The treatment of petrochemical wastewater via ozone-persulfate coupled catalytic oxidation: mechanism of removal of soluble organic matter.

Petrochemical wastewater contains a variety of organic pollutants. Advanced oxidation processes (AOPs) are used for deep petrochemical wastewater treatment with distinct advantages, including the complete mineralization of organic substances, minimal residual byproducts, and compatibility with biological treatment systems. This work evaluates the effectiveness of three methods, namely, ozone, persulfate, and O3-PMS (ozone-persulfate) processes, which were compared to remove soluble organic matter. The O3-PMS process offered significant advantages in terms of organic matter removal efficiency. This process involves ozone dissolution in an aqueous persulfate solution, producing a more significant amount of hydroxyl radicals in comparison to single AOPs. The production of hydroxyl radicals and the synergistic effect of hydroxyl radicals and persulfate radicals were investigated. In the O3-PMS process, transition metal ions were added to understand the mechanism of the O3-PMS coupled catalytic oxidation system. The results showed that when the ozone concentration was in the range of 5 ~ 25 mg/L, the dosage of persulfate was in the range of 0.01 ~ 0.05 mol/L, the dosage of metal compounds was in the range of 0:0 ~ 2:1, and the reaction time was in the range of 0 ~ 2 h; the optimum chemical oxygen demand (CODCr) and total organic content (TOC) removal effect was achieved under the coupled system with an ozone concentration of 10 mg/L, a persulfate dosage of 0.02 mol/L, a 1:2 dosage ratio of between Fe2+ and Cu2+ compounds, and a reaction time of 2 h. Under optimal reaction conditions, the rates of CODCr and TOC removal reached 70% and 79.3%, respectively. Furthermore, the removal kinetics of the O3-PMS coupled catalytic oxidation system was analyzed to optimize the removal conditions of COD and TOC, and the mechanism regulating the degradation of dissolved organic matter was explored by three-dimensional fluorescence and GC-MS technology. Thus, O3-PMS coupled catalytic oxidation is an effective process for the deep treatment of wastewater. The careful selection of transition metal ions serves as a theoretical foundation for the subsequent preparation of catalysts for the ozone persulfate oxidation system, and this study provides a suitable reference for removing organic matter from petrochemical wastewater.

DeepFGRN: inference of gene regulatory network with regulation type based on directed graph embedding.

The inference of gene regulatory networks (GRNs) from gene expression profiles has been a key issue in systems biology, prompting many researchers to develop diverse computational methods. However, most of these methods do not reconstruct directed GRNs with regulatory types because of the lack of benchmark datasets or defects in the computational methods. Here, we collect benchmark datasets and propose a deep learning-based model, DeepFGRN, for reconstructing fine gene regulatory networks (FGRNs) with both regulation types and directions. In addition, the GRNs of real species are always large graphs with direction and high sparsity, which impede the advancement of GRN inference. Therefore, DeepFGRN builds a node bidirectional representation module to capture the directed graph embedding representation of the GRN. Specifically, the source and target generators are designed to learn the low-dimensional dense embedding of the source and target neighbors of a gene, respectively. An adversarial learning strategy is applied to iteratively learn the real neighbors of each gene. In addition, because the expression profiles of genes with regulatory associations are correlative, a correlation analysis module is designed. Specifically, this module not only fully extracts gene expression features, but also captures the correlation between regulators and target genes. Experimental results show that DeepFGRN has a competitive capability for both GRN and FGRN inference. Potential biomarkers and therapeutic drugs for breast cancer, liver cancer, lung cancer and coronavirus disease 2019 are identified based on the candidate FGRNs, providing a possible opportunity to advance our knowledge of disease treatments.

Right ventricular volume and function by three-dimensional echocardiography: results of the echocardiographic measurements in normal Chinese adults (EMINCA) II.

Three-dimensional (3D) echocardiography is an emerging technique for assessing right ventricular (RV) volume and function, but 3D-RV normal values from a large Chinese population are still lacking. The aim of the present study was to establish normal values of 3D-RV volume and function in healthy Chinese volunteers. A total of 1117 Han Chinese volunteers from 28 laboratories in 20 provinces of China were enrolled, and 3D-RV images of 747 volunteers with optimal image quality were ultimately analyzed by a core laboratory. Both vendor-dependent and vendor-independent software platforms were used to analyze the 3D-RV images. We found that men had larger RV volumes than women did in the whole population, even after indexing to body surface area, and older individuals had smaller RV volumes. The normal RV volume was significantly smaller than that recommended by the American Society of Echocardiography/European Association of Cardiovascular Imaging guidelines in both sexes. There were significant differences in 3D-RV measurements between the two vendor ultrasound systems and the different software platforms. The echocardiographic measurements in normal Chinese adults II study revealed normal 3D-RV volume and function in a large Chinese population, and there were significant differences between the sexes, ages, races, and vendor groups. Thus, normal 3D-RV values should be stratified by sex, age, race, and vendor.

PMMNet: A Dual Branch Fusion Network of Point Cloud and Multi-View for Intracranial Aneurysm Classification and Segmentation.

Intracranial aneurysm (IA) is a vascular disease of the brain arteries caused by pathological vascular dilation, which can result in subarachnoid hemorrhage if ruptured. Automatically classification and segmentation of intracranial aneurysms are essential for their diagnosis and treatment. However, the majority of current research is focused on two-dimensional images, ignoring the 3D spatial information that is also critical. In this work, we propose a novel dual-branch fusion network called the Point Cloud and Multi-View Medical Neural Network (PMMNet) for IA classification and segmentation. Specifically, one branch based on 3D point clouds serves the purpose of extracting spatial features, whereas the other branch based on multi-view images acquires 2D pixel features. Ultimately, the two types of features are fused for IA classification and segmentation. To extract both local and global features from 3D point clouds, Multilayer Perceptron (MLP) and the attention mechanism are used in parallel. In addition, a SPSA module is proposed for multi-view image feature learning, which extracts more exquisite channel and spatial multi-scale features from 2D images. Experiments conducted on the IntrA dataset outperform other state-of-the-art methods, demonstrating that the proposed PMMNet exhibits strong superiority on the medical 3D dataset. We also obtain competitive results on public datasets, including ModelNet40, ModelNet10, and ShapeNetPart, which further validate the robustness and generality of the PMMNet.

Multistimuli-Responsive Shape-Memory Composites with a Water-Assisted Self-Healing Function Based on Sodium Carboxymethyl Cellulose/Poly(vinyl alcohol)/MXene.

Recent advancements in artificial intelligence have propelled the development of shape-memory polymers (SMPs) with sophisticated, environment-sensitive capabilities. Despite the progress, most of the existing SMPs are limited to responding to a single stimulus and show poor functionality, which has severely hindered their future applications. Herein, we report a high-performance multistimuli-responsive shape-memory and self-healing composite film fabricated by embedding MXene nanosheets into a conventional shape-memory sodium carboxymethyl cellulose (CMC) and poly(vinyl alcohol) (PVA) matrix. The incorporation of photothermal MXene nanosheets not only enhances the composite films' mechanical strength but also provides efficient solar-thermal conversion and robust light-actuated shape-memory properties. The resultant composite films exhibit an exceptional shape-memory response to various stimuli including heat, light, and water. Meanwhile, the interfacial interactions can be modulated by adjusting the MXene content, thereby enabling precise manipulation of the shape-memory performance. Moreover, thanks to the intrinsic hydrophilicity of the components and the unique physically cross-linked network, the composite films also demonstrate an effective water-assisted self-healing capability with an impressive healing efficiency of 85.7%. This work offers insights into the development of multifunctional, multistimuli-responsive shape-memory composites, opening up new possibilities for future applications in smart technologies.

Neural Signatures of Competition between Voluntary and Involuntary Influences over the Focus of Attention in Visual Working Memory.

Adaptive behavior relies on the selection and prioritization of relevant sensory inputs from the external environment as well as from among internal sensory representations held in working memory. Recent behavioral evidence suggests that the classic distinction between voluntary (goal-driven) and involuntary (stimulus-driven) influences over attentional allocation also applies to the selection of internal representations held in working memory. In the current EEG study, we set out to investigate the neural dynamics associated with the competition between voluntary and involuntary control over the focus of attention in visual working memory. We show that when voluntary and involuntary factors compete for the internal focus of attention, prioritization of the appropriate item is delayed-as reflected both in delayed gaze biases that track internal selection and in delayed neural beta (15-25 Hz) dynamics that track the planning for the upcoming memory-guided manual action. We further show how this competition is paralleled-possibly resolved-by an increase in frontal midline theta (4-8 Hz) activity that, moreover, predicts the speed of ensuing memory-guided behavior. Finally, because theta increased following retrocues that effectively reduced working-memory load, our data unveil how frontal theta activity during internal attentional focusing tracks demands on cognitive control over and above working-memory load. Together, these data yield new insight into the neural dynamics that govern the focus of attention in visual working memory, and disentangle the contributions of frontal midline theta activity to the processes of control versus retention in working memory.

Changes in the cellular makeup of motor patterning circuits drive courtship song evolution in Drosophila.

How evolutionary changes in genes and neurons encode species variation in complex motor behaviors are largely unknown. Here, we develop genetic tools that permit a neural circuit comparison between the model species Drosophila melanogaster and the closely-related species D. yakuba, who has undergone a lineage-specific loss of sine song, one of the two major types of male courtship song in Drosophila. Neuroanatomical comparison of song patterning neurons called TN1 across the phylogeny demonstrates a link between the loss of sine song and a reduction both in the number of TN1 neurons and the neurites serving the sine circuit connectivity. Optogenetic activation confirms that TN1 neurons in D. yakuba have lost the ability to drive sine song, while maintaining the ability to drive the singing wing posture. Single-cell transcriptomic comparison shows that D. yakuba specifically lacks a cell type corresponding to TN1A neurons, the TN1 subtype that is essential for sine song. Genetic and developmental manipulation reveals a functional divergence of the sex determination gene doublesex in D. yakuba to reduce TN1 number by promoting apoptosis. Our work illustrates the contribution of motor patterning circuits and cell type changes in behavioral evolution, and uncovers the evolutionary lability of sex determination genes to reconfigure the cellular makeup of neural circuits.

Dual cytoplasmic-peroxisomal compartmentalization engineering and multiple metabolic engineering strategies for high yield non-psychoactive cannabinoid in Saccharomyces cerevisiae.

CBG (Cannabigerol), a nonpsychoactive cannabinoid, has garnered attention due to its extensive antimicrobial and anti-inflammatory properties. However, the natural content of CBG in Cannabis sativa L. is minimal. In this study, we developed an engineered cell factory for CBG production using Saccharomyces cerevisiae. We introduced the CBGA biosynthetic pathway into S. cerevisiae and employed several strategies to enhance CBGA production. These strategies included dynamically inhibiting the competitive bypass of key metabolic pathways regulated by Erg20p. Additionally, we implemented a dual cytoplasmic-peroxisomal compartmentalization approach to further increase CBGA production. Furthermore, we ensured efficient CBGA production by optimizing NADPH and acetyl-CoA pools. Ultimately, our engineered strain achieved a CBG titer of 138 mg L-1 through fed-batch fermentation in a 5 L bioreactor, facilitated by microwave decarboxylation extraction. These findings underscore the significant potential of yeast cell factories for achieving higher yields in cannabinoid production.

[MiR-217 Targeting PI3K/Akt Pathway Enhances Sensitivity of Adriamycin to Acute Myeloid Leukemia].

OBJECTIVE: To investigate the effects of miR-217 on proliferation and adriamycin sensitivity of acute myeloid leukemia (AML) cells. METHODS: The mimic NC and miR-217 mimic vectors were constructed and transfected into HL-60 cells, and transfection efficiency was detected by qPCR. The cells were treated with different concentrations of adriamycin for 24 h and 48 h. CCK-8 assay was used to detect the chemical sensitivity of adriamycin and screen the optimal concentration and time of adriamycin treatment. Cells were divided into control group, mimic NC group, miR-217 mimic group, adriamycin group and miR-217 mimic+adriamycin group. Apoptosis was detected by flow cytometry, and the expressions of miR-217, PI3K and Akt3 were detected by qPCR. Western blot was used to detect the expression of PI3K/Akt pathway proteins PI3K, Akt3 and apoptosis proteins Bcl-2, Bax, and double luciferase was used to verify the relationship between miR-217 and Akt3. RESULTS: MiR-217 mimic could enhance the sensitivity of HL-60 cells to adriamycin. The optimal concentration and treatment time of adriamycin were 160 ng/ml and 48 h, respectively. Compared with control group, apoptosis rate, miR-217 and Bax protein levels were significantly increased in miR-217 mimic and adriamycin groups (P < 0.01), while Bcl-2 protein, PI3K, Akt3 mRNA and protein levels were significantly decreased (P < 0.01). Compared with adriamycin group, apoptosis rate, miR-217 and Bax protein levels were significantly increased in miR-217 mimic+adriamycin group (P < 0.01), while Bcl-2 protein, PI3K, Akt3 mRNA and protein levels were significantly decreased (P < 0.01). Dual luciferase assay showed that there was a targeted regulatory relationship between miR-217 and Akt3. CONCLUSION: MiR-217 regulates the PI3K/Akt pathway targeting Akt3, inhibits cell proliferation, promotes cell apoptosis and enhances the sensitivity of adriamycin to AML cells.

A Molecular Cage Accessed by Threefold Click Reaction of a C3v-Symmetric Triazido-Functionalized Tribenzotriquinacene.

The hitherto unknown hexakis(halomethyl)-functionalized tribenzotriquinacenes (TBTQs) 9 and 10 were synthesized from the key 4b,8b,12b-tribromo-TBTQ derivative 6 by an improved route in 67% overall yield. Extension of the bowl-shaped framework of 9 or 10 by threefold condensation with propargylamine or 2-azidoethylamine afforded the corresponding TBTQ-trialkyne 11 and TBTQ-triazide 12, respectively. While attempts to construct bis-TBTQ cages, including homodimerization of 11 and heterocoupling of 11 with 12, were unsuccessful, triazide 12 was found to undergo threefold [3 + 2]-cycloaddition with 3-ethynylaniline and phloroglucinol tripropargyl ether under click chemistry conditions. The latter reaction enabled facile capping of the TBTQ bowl to give the novel cage compound 5 in 22% yield.

Effectiveness of the "Hand as Foot" teaching method in human physiology: A randomized controlled trial.

BACKGROUND: The "Hand as Foot" teaching method, an innovative approach in medical education, utilizes hand gestures to simulate anatomical structures and functions. This study aimed to assess the effectiveness of the "Hand as Foot" teaching method compared to traditional method in the "Human Physiology" course. METHODS: During the 2023 spring semester, a randomized controlled trial involved 84 health management students. Participants were randomly assigned to the "Hand as Foot" teaching group or the traditional teaching group. A self-designed Likert scale was used to evaluate students' perceptions of teaching effectiveness, covering dimensions such as engagingness, intuitiveness, facilitation of understanding, enhancement of memorization, and effortlessness of learning. Additionally, a knowledge assessment test was administered to measure knowledge acquisition. RESULTS: The "Hand as Foot teaching method" group (41 students) reported significantly higher ratings for all dimensions of teaching effectiveness compared to the traditional teaching group (43 students) (p ≤ 0.01). Despite the lack of statistical significance, the experimental group's test scores were notably superior (Mean = 6.35 vs. Mean = 5.94). DISCUSSION: The "Hand as Foot" teaching method demonstrated superior effectiveness in engaging students, facilitating comprehension, and enhancing memorization. Its interactive and tangible nature provided a holistic learning experience, enabling students to visualize complex physiological mechanisms. Additionally, it fostered active student participation and a desire for deeper understanding. CONCLUSION: While the "Hand as Foot" teaching method demonstrated strengths in engaging students and aiding comprehension, further researches with larger and diverse cohorts are needed to gauge its impact on learning outcomes and broader applicability.

LINC02561 promotes metastasis in HCC via HIF1-α/NDRG1/UPF1 axis.

In the entire world, hepatocellular carcinoma (HCC) is one of the most frequent cancers that lead to death. Experiments on the function of long non-coding RNAs in the emergence of malignancies, including HCC, are ongoing. As a crucial RNA monitoring mechanism in eucaryotic cells, nonsense-mediated mRNA decay (NMD) can recognize and destroy mRNAs, which has an premature termination codons (PTC) in the open reading frame to prevent harmful buildup of truncated protein products in the cells. Nonsense transcript regulator 1 (Up-frameshift suppressor 1, UPF1), as a highly conserved RNA helicase and ATPase, plays a key role in NMD. Our laboratory screened out the highly expressed lncRNA LINC02561 in HCC from the TCGA database. Further research found that LINC02561 enhanced the invasion and transition abilities of liver cancer cells by regulating the protein N-Myc downstream regulated 1 (NDRG1). Hypoxia inducible factor-1 (HIF-1α) can bonded to LINC02561 promoters under hypoxic conditions, thereby promoting the upregulation of LINC02561 expression in liver cancer cells. LINC02561 competes with NDRG1 mRNA to bind UPF1, thereby preventing the degradation of NDRG1 mRNA to facilitate NDRG1 protein level. Taken together, the HIF1α-LINC02561-UPF1-NDRG1 regulatory axis could be an entirely novel target of liver cancer-related treatment.

Rutin, Puerarin and Silymarin Regulated Aluminum-Induced Imbalance of Neurotransmitters and Metal Elements in Brain of Rats.

Non-specifically binding of aluminum to various substances in the organism can result in toxicity. The accumulation of large amounts of aluminum can cause an imbalance in metal homeostasis and interfere with the synthesis and release of neurotransmitters. Flavonoids have strong metal chelating activity, which can reduce damage to the central nervous system. The purpose of this study was to investigate the protective effect of three representative flavonoids, rutin, puerarin and silymarin, on the brain toxicity induced by long-term exposure to aluminum trichloride (AlCl3). Sixty-four Wistar rats were randomly divided into eight groups (n = 8). The rats in six intervention groups were given 100 or 200 mg/kg BW/day of three different flavonoids for four weeks after a 4-week exposure to 281.40 mg/kg BW/day AlCl3·6H2O, while the rats in the AlCl3-toxicity and control groups were given the vehicle after the period of AlCl3 exposure. The results showed that rutin, puerarin, and silymarin could increase the concentrations of magnesium, iron, and zinc in the brains of the rats. Moreover, the intake of these three flavonoids regulated the homeostasis of amino acid neurotransmitters and adjusted the concentrations of monoamine neurotransmitters to normal levels. Taken together, our data suggest that rutin, puerarin, and silymarin could ameliorate AlCl3-induced brain toxicity in the rats by regulating imbalance of metal elements and neurotransmitters in the brains of rats.

Efficacy and safety of autologous platelet-rich plasma for diabetic foot ulcers: a systematic review and meta-analysis.

OBJECTIVE: To investigate the efficacy and safety of autologous platelet-rich plasma (au-PRP) for diabetic foot ulcer (DFU) treatment. METHOD: We conducted database searches (MEDLINE, EMBASE, evidence-based medicine reviews: CENTRAL, PubMed, and Web of Science) and reference mining for randomised controlled trials from inception to 23 January 2022. Results were scrutinised, data were extracted and research quality was investigated by two independent authors. Primary outcome was the proportion of complete ulcer healing. Secondary outcomes included both the mean time to complete healing and the incidence of adverse events. Statistical analyses were performed in RevMan 5.4 (Cochrane, UK). Kaplan-Meier curves for time to complete healing were pooled in R software (version 4.1.2) (R Foundation, Austria). RESULTS: Of the 231 records identified, 17 studies with a total of 1303 participants (649 randomised to the au-PRP group and 654 to a standard of care (SOC) group) met the eligibility criteria and were included in our study. Compared with SOC, au-PRP appeared to promote the complete healing rate (odds ratio (OR): 2.11; 95% Confidence Interval: 1.55-2.86). Au-PRP also appeared to significantly shorten complete healing time (mean duration: -19.04 days; 95%CI: -20.46--17.61]). There was no significant difference on adverse events. Results were robust on sensitivity analyses. CONCLUSION: Based on the findings of this review and meta-analysis, Au-PRP is an effective and safe adjuvant therapy for DFUs.

[Effect of Long Non-Coding RNA LINC01268 on the Malignant Biological Behaviors of Acute Myeloid Leukemia Cells].

OBJECTIVE: To investigate the effect of long non-coding RNA LINC01268 on apoptosis of acute myeloid leukemia (AML) cells and related mechanisms. METHODS: The expression levels of LINC01268 and miR-217 in peripheral blood samples from AML patients and AML cell lines HL-60 and KG-1 were detected by qRT-PCR. HL-60 cells were divided into pcDNA3.1-NC, pcDNA3.1-LINC01268, si-NC, si-LINC01268, miR-NC, miR-217 mimics, si-LINC01268 + inhibitor-NC and si-LINC01268+ miR-217 inhibitor groups. The mRNA expressions of LINC01268 and miR-217 were detected by qRT-PCR. The targeting relationship between LINC01268 and miR-217 was detected by dual-luciferase reporter assay. Cell viability was detected by CCK-8 assay. Cell cycle distribution and apoptosis were detected by flow cytometry. The expression of cell cycle and apoptosis-related proteins p21, Bcl-2, Bax, caspase-3 and PI3K/AKT signaling pathway-related proteins were detected by Western blot. RESULTS: The expression of LINC01268 in peripheral blood samples of AML patients and AML cell lines HL-60 and KG-1 was increased (P < 0.05), and the expression of miR-217 was decreased (P < 0.05). Compared with si-NC group and miR-NC group, the viability of HL-60 cells was decreased in si-LINC01268 group and miR-217 mimics group (P < 0.05), the proportion of cells in G1 phase and apoptosis rate were increased (P < 0.05), the protein expression levels of p21, Bax and caspase-3 were increased (P < 0.05), while the protein expression level of Bcl-2 was decreased (P < 0.05). LINC01268 targeted and negatively regulated the expression of miR-217, and inhibiting the expression of miR-217 partially reversed the effects of LINC01268 interference on the viability, cell cycle and apoptosis of HL-60 cells. Interference with LINC01268 could inhibit the activity of PI3K/AKT signaling pathway. Inhibiting the expression of miR-217 could partially reverse the inhibition of LINC01268 interference on PI3K/AKT signaling pathway. CONCLUSION: LINC01268 is highly expressed and miR-217 is lowly expressed in AML cells. LINC01268 can promote the activity of PI3K/AKT signaling pathway, increase the survival rate and inhibit the apoptosis of AML cells by targeting miR-217 expression.

Ancestral neural circuits potentiate the origin of a female sexual behavior.

Courtship interactions are remarkably diverse in form and complexity among species. How neural circuits evolve to encode new behaviors that are functionally integrated into these dynamic social interactions is unknown. Here we report a recently originated female sexual behavior in the island endemic Drosophila species D. santomea, where females signal receptivity to male courtship songs by spreading their wings, which in turn promotes prolonged songs in courting males. Copulation success depends on this female signal and correlates with males' ability to adjust his singing in such a social feedback loop. Functional comparison of sexual circuitry across species suggests that a pair of descending neurons, which integrates male song stimuli and female internal state to control a conserved female abdominal behavior, drives wing spreading in D. santomea. This co-option occurred through the refinement of a pre-existing, plastic circuit that can be optogenetically activated in an outgroup species. Combined, our results show that the ancestral potential of a socially-tuned key circuit node to engage the wing motor program facilitates the expression of a new female behavior in appropriate sensory and motivational contexts. More broadly, our work provides insights into the evolution of social behaviors, particularly female behaviors, and the underlying neural mechanisms.

CFANet: Context Feature Fusion and Attention Mechanism Based Network for Small Target Segmentation in Medical Images.

Medical image segmentation plays a crucial role in clinical diagnosis, treatment planning, and disease monitoring. The automatic segmentation method based on deep learning has developed rapidly, with segmentation results comparable to clinical experts for large objects, but the segmentation accuracy for small objects is still unsatisfactory. Current segmentation methods based on deep learning find it difficult to extract multiple scale features of medical images, leading to an insufficient detection capability for smaller objects. In this paper, we propose a context feature fusion and attention mechanism based network for small target segmentation in medical images called CFANet. CFANet is based on U-Net structure, including the encoder and the decoder, and incorporates two key modules, context feature fusion (CFF) and effective channel spatial attention (ECSA), in order to improve segmentation performance. The CFF module utilizes contextual information from different scales to enhance the representation of small targets. By fusing multi-scale features, the network captures local and global contextual cues, which are critical for accurate segmentation. The ECSA module further enhances the network's ability to capture long-range dependencies by incorporating attention mechanisms at the spatial and channel levels, which allows the network to focus on information-rich regions while suppressing irrelevant or noisy features. Extensive experiments are conducted on four challenging medical image datasets, namely ADAM, LUNA16, Thoracic OAR, and WORD. Experimental results show that CFANet outperforms state-of-the-art methods in terms of segmentation accuracy and robustness. The proposed method achieves excellent performance in segmenting small targets in medical images, demonstrating its potential in various clinical applications.

High-throughput quantitation of amino acids and acylcarnitine in cerebrospinal fluid: identification of PCNSL biomarkers and potential metabolic messengers.

Background: Due to the poor prognosis and rising occurrence, there is a crucial need to improve the diagnosis of Primary Central Nervous System Lymphoma (PCNSL), which is a rare type of non-Hodgkin's lymphoma. This study utilized targeted metabolomics of cerebrospinal fluid (CSF) to identify biomarker panels for the improved diagnosis or differential diagnosis of primary central nervous system lymphoma (PCNSL). Methods: In this study, a cohort of 68 individuals, including patients with primary central nervous system lymphoma (PCNSL), non-malignant disease controls, and patients with other brain tumors, was recruited. Their cerebrospinal fluid samples were analyzed using the Ultra-high performance liquid chromatography - tandem mass spectrometer (UHPLC-MS/MS) technique for targeted metabolomics analysis. Multivariate statistical analysis and logistic regression modeling were employed to identify biomarkers for both diagnosis (Dx) and differential diagnosis (Diff) purposes. The Dx and Diff models were further validated using a separate cohort of 34 subjects through logistic regression modeling. Results: A targeted analysis of 45 metabolites was conducted using UHPLC-MS/MS on cerebrospinal fluid (CSF) samples from a cohort of 68 individuals, including PCNSL patients, non-malignant disease controls, and patients with other brain tumors. Five metabolic features were identified as biomarkers for PCNSL diagnosis, while nine metabolic features were found to be biomarkers for differential diagnosis. Logistic regression modeling was employed to validate the Dx and Diff models using an independent cohort of 34 subjects. The logistic model demonstrated excellent performance, with an AUC of 0.83 for PCNSL vs. non-malignant disease controls and 0.86 for PCNSL vs. other brain tumor patients. Conclusion: Our study has successfully developed two logistic regression models utilizing metabolic markers in cerebrospinal fluid (CSF) for the diagnosis and differential diagnosis of PCNSL. These models provide valuable insights and hold promise for the future development of a non-invasive and reliable diagnostic tool for PCNSL.

FFMAVP: a new classifier based on feature fusion and multitask learning for identifying antiviral peptides and their subclasses.

Antiviral peptides (AVPs) are widely found in animals and plants, with high specificity and strong sensitivity to drug-resistant viruses. However, due to the great heterogeneity of different viruses, most of the AVPs have specific antiviral activities. Therefore, it is necessary to identify the specific activities of AVPs on virus types. Most existing studies only identify AVPs, with only a few studies identifying subclasses by training multiple binary classifiers. We develop a two-stage prediction tool named FFMAVP that can simultaneously predict AVPs and their subclasses. In the first stage, we identify whether a peptide is AVP or not. In the second stage, we predict the six virus families and eight species specifically targeted by AVPs based on two multiclass tasks. Specifically, the feature extraction module in the two-stage task of FFMAVP adopts the same neural network structure, in which one branch extracts features based on amino acid feature descriptors and the other branch extracts sequence features. Then, the two types of features are fused for the following task. Considering the correlation between the two tasks of the second stage, a multitask learning model is constructed to improve the effectiveness of the two multiclass tasks. In addition, to improve the effectiveness of the second stage, the network parameters trained through the first-stage data are used to initialize the network parameters in the second stage. As a demonstration, the cross-validation results, independent test results and visualization results show that FFMAVP achieves great advantages in both stages.