High-Branched Natural Polysaccharide Flaxseed Gum Binder for Silicon-Based Lithium-Ion Batteries with High Capacity.

Silicon-based anodes heavily depend on the binder to preserve the unbroken electrode structure. In the present work, natural flaxseed gum (FG) is used as a binder of silicon nanoparticles (SiNPs) anode for the first time. Owing to a large number of polar groups and a rich branched structure, this material not only anchors tightly to the surface of SiNPs through bonding interactions but also formed a hydrogen bonding network structure among molecules. As a result, the FG binder can endow the silicon electrode with stable interfacial adhesion and outstanding mechanical properties. In addition, FG with a high viscosity facilitates the homogeneous dispersion of the electrode components. When FG is used as a binder, the cycling performance of the Si anode is greatly improved. After one hundred cycles at an applied current density of 1 A g-1, the electrode continues to display remarkable electrochemical properties with a significant cyclic capacity (2213 mA h g-1) and initial Coulombic efficiency (ICE) of 89.7%.

Discovery of the Highly Selective and Potent STAT3 Inhibitor for Pancreatic Cancer Treatment.

Signal transducer and activator of transcription 3 (STAT3) is an attractive cancer therapeutic target. Unfortunately, targeting STAT3 with small molecules has proven to be very challenging, and for full activation of STAT3, the cooperative phosphorylation of both tyrosine 705 (Tyr705) and serine 727 (Ser727) is needed. Further, a selective inhibitor of STAT3 dual phosphorylation has not been developed. Here, we identified a low nanomolar potency and highly selective small-molecule STAT3 inhibitor that simultaneously inhibits both STAT3 Tyr705 and Ser727 phosphorylation. YY002 potently inhibited STAT3-dependent tumor cell growth in vitro and achieved potent suppression of tumor growth and metastasis in vivo. More importantly, YY002 exhibited favorable pharmacokinetics, an acceptable safety profile, and superior antitumor efficacy compared to BBI608 (STAT3 inhibitor that has advanced into phase III trials). For the mechanism, YY002 is selectively bound to the STAT3 Src Homology 2 (SH2) domain over other STAT members, which strongly suppressed STAT3 nuclear and mitochondrial functions in STAT3-dependent cells. Collectively, this study suggests the potential of small-molecule STAT3 inhibitors as possible anticancer therapeutic agents.

A tale of two tumors: differential, but detrimental, effects of glioblastoma extracellular vesicles (EVs) on normal human brain cells.

Glioblastomas (GBMs) are dreadful brain tumors with abysmal survival outcomes. GBM EVs dramatically affect normal brain cells (largely astrocytes) constituting the tumor microenvironment (TME). EVs from different patient-derived GBM spheroids induced differential transcriptomic, secretomic, and proteomic effects on cultured astrocytes/brain tissue slices as GBM EV recipients. The net outcome of brain cell differential changes nonetheless converges on increased tumorigenicity. GBM spheroids and brain slices were derived from neurosurgical patient tissues following informed consent. Astrocytes were commercially obtained. EVs were isolated from conditioned culture media by ultrafiltration, ultraconcentration, and ultracentrifugation. EVs were characterized by nanoparticle tracking analysis, electron microscopy, biochemical markers, and proteomics. Astrocytes/brain tissues were treated with GBM EVs before downstream analyses. EVs from different GBMs induced brain cells to alter secretomes with pro-inflammatory or TME-modifying (proteolytic) effects. Astrocyte responses ranged from anti-viral gene/protein expression and cytokine release to altered extracellular signal-regulated protein kinase (ERK1/2) signaling pathways, and conditioned media from EV-treated cells increased GBM cell proliferation. Thus, astrocytes/brain slices treated with different GBM EVs underwent non-identical changes in various 'omics readouts and other assays, indicating "personalized" tumor-specific GBM EV effects on the TME. This raises concern regarding reliance on "model" systems as a sole basis for translational direction. Nonetheless, net downstream impacts from differential cellular and TME effects still led to increased tumorigenic capacities for the different GBMs.

Investigating genetic links between blood metabolites and preeclampsia.

BACKGROUND: Observational studies have revealed that metabolic disorders are closely related to the development of preeclampsia (PE). However, there is still a research gap on the causal role of metabolites in promoting or preventing PE. We aimed to systematically explore the causal association between circulating metabolites and PE. METHODS: Single nucleotide polymorphisms (SNPs) from genome-wide association study (GWAS) of 486 blood metabolites (7,824 participants) were extracted as instrumental variables (P < 1 × 10- 5), GWAS summary statistics for PE were obtained from FinnGen consortium (7,212 cases and 194,266 controls) as outcome, and a two-sample Mendelian randomization (MR) analysis was conducted. Inverse variance weighted (IVW) was set as the primary method, with MR-Egger and weighted median as auxiliary methods; the instrumental variable strength and confounding factors were also assessed. Sensitivity analyses including MR-Egger, Cochran's Q test, MR-PRESSO and leave-one-out analysis were performed to test the robustness of the MR results. For significant associations, repeated MR and meta-analysis were performed by another metabolite GWAS (8,299 participants). Furthermore, significantly associated metabolites were subjected to a metabolic pathway analysis. RESULTS: The instrumental variables for the metabolites ranged from 3 to 493. Primary analysis revealed a total of 12 known (e.g., phenol sulfate, citrulline, lactate and gamma-glutamylglutamine) and 11 unknown metabolites were associated with PE. Heterogeneity and pleiotropy tests verified the robustness of the MR results. Validation with another metabolite GWAS dataset revealed consistency trends in 6 of the known metabolites with preliminary analysis, particularly the finding that genetic susceptibility to low levels of arachidonate (20:4n6) and citrulline were risk factors for PE. The pathway analysis revealed glycolysis/gluconeogenesis and arginine biosynthesis involved in the pathogenesis of PE. CONCLUSIONS: This study identifies a causal relationship between some circulating metabolites and PE. Our study presented new perspectives on the pathogenesis of PE by integrating metabolomics with genomics, which opens up avenues for more accurate understanding and management of the disease, providing new potential candidate metabolic molecular markers for the prevention, diagnosis and treatment of PE. Considering the limitations of MR studies, further research is needed to confirm the causality and underlying mechanisms of these findings.

Four-year variation in pathogen distribution and antimicrobial susceptibility of urosepsis: a single-center retrospective analysis.

Background: Urosepsis is a common disease in urology, which is characterized by high treatment costs and high mortality. In the treatment of sepsis, anti-infection therapy is the most important means. However, the effect of empirical anti-infection therapy is often not ideal. Therefore, it is necessary to continuously monitor the prevalence of bacterial isolates in the blood culture of patients with urinary sepsis and their sensitivity to antibacterial drugs. This is of great significance to improve the efficacy of empirical antibiotic therapy for urosepsis. Objective: To elucidate the landscape of prevailing bacterial profiles and their antimicrobial susceptibilities in urosepsis cases, and to furnish robust clinical evidence to underpin the timely initiation of empirical antibiotic treatment. Methods: Collect the basic information and blood culture results of patients with urosepsis hospitalized from 2017 to 2020. Retrospective analysis of bacterial species and antimicrobial susceptibility in urosepsis and changes over 4 years. Results: Gram-negative bacteria (178 isolates, 75.11%) constituted the main pathogens causing urosepsis, followed by Gram-positive bacteria (46 isolates, 19.41%) and fungus (13 isolates, 5.48%). The sensitivity of ertapenem, meropenem, amikacin, and imipenem to Gram-negative bacteria all exceeded 85%. The sensitivity rates of levofloxacin, gentamicin, and ciprofloxacin are decreasing every year (p < 0.05). Tigecycline, vancomycin, and linezolid exhibited excellent sensitivity against Gram-positive bacteria. Among fungi, fluconazole demonstrated universal sensitivity, while itraconazole-resistant isolates have been found, and amphotericin B is still effective. Conclusion: Analysis of blood culture results of patients more accurately reflected the etiology of urosepsis, mainly Escherichia coli, Enterococcus, and Klebsiella pneumoniae. If there are no definitive blood culture results, empiric treatment of urosepsis should not include fluoroquinolone antibiotics. Cefepime, cefoxitin, and ceftazidime are the most sensitive antibiotics to Gram-negative bacteria besides carbapenem antibiotics. In addition, the current situation regarding extended-spectrum ß-lactamase-producing bacteria and carbapenem-resistant Enterobacteriaceae bacteria resistance is extremely concerning with limited therapeutic options available. Strengthening antibiotic management practices and exploring novel antibacterial agents can help mitigate this issue.

ControlFace: Feature Disentangling for Controllable Face Swapping.

Face swapping is an intriguing and intricate task in the field of computer vision. Currently, most mainstream face swapping methods employ face recognition models to extract identity features and inject them into the generation process. Nonetheless, such methods often struggle to effectively transfer identity information, which leads to generated results failing to achieve a high identity similarity to the source face. Furthermore, if we can accurately disentangle identity information, we can achieve controllable face swapping, thereby providing more choices to users. In pursuit of this goal, we propose a new face swapping framework (ControlFace) based on the disentanglement of identity information. We disentangle the structure and texture of the source face, encoding and characterizing them in the form of feature embeddings separately. According to the semantic level of each feature representation, we inject them into the corresponding feature mapper and fuse them adequately in the latent space of StyleGAN. Owing to such disentanglement of structure and texture, we are able to controllably transfer parts of the identity features. Extensive experiments and comparisons with state-of-the-art face swapping methods demonstrate the superiority of our face swapping framework in terms of transferring identity information, producing high-quality face images, and controllable face swapping.

WB518, a novel STAT3 inhibitor, effectively alleviates IMQ and TPA-induced animal psoriasis by inhibiting STAT3 phosphorylation and Keratin 17.

OBJECTIVES: Psoriasis is a prevalent chronic inflammatory skin disease in humans that is characterized by frequent relapses and challenging to cure. WB518 is a novel small molecule compound with an undisclosed structure. Therefore, our study aimed to investigate the therapeutic potential of WB518 in vitro and in vivo for the treatment of psoriasis, specifically targeting the abnormal proliferation, aberrant differentiation of epidermal keratinocytes, and pathogenic inflammatory response. MATERIALS AND METHODS: We employed dual luciferase reporter assay to screen compounds capable of inhibiting STAT3 gene transcription. Flow cytometry was utilized to analyze CD3-positive cells. Protein and mRNA levels were assessed through Western blotting, immunofluorescence, immunohistochemistry, and real-time PCR. Cell viability was measured using the MTS assay, while in vivo models of psoriasis induced by IMQ and TPA were employed to study the anti-psoriasis effect of WB518. RESULTS: WB518 was found to significantly reduce the mRNA and protein levels of Keratin 17 (K17) in HaCaT cells by inhibiting the phosphorylation of STAT3 Tyr705 (Y705). In the IMQ and TPA-induced psoriasis mouse model, WB518 effectively improved scaling, epidermal hyperplasia, and inflammation. WB518 also suppressed the expression of inflammatory cytokines, such as interleukin (IL)-1ß, IL-6, IL-17, and IL-23. Furthermore, WB518 decreased the proportion of CD3-positive cells in the psoriatic skin of mice. CONCLUSIONS: WB518 exhibits promising potential as a treatment candidate for psoriasis.

Deep Image Matting With Sparse User Interactions.

Image matting is a fundamental and challenging problem in computer vision and graphics. Most existing matting methods leverage a user-supplied trimap as an auxiliary input to produce good alpha matte. However, obtaining high-quality trimap itself is arduous. Recently, some hint-free methods have emerged, however, the matting quality is still far behind the trimap-based methods. The main reason is that, some hints for removing semantic ambiguity and improving matting quality are essential. Apparently, there is a trade-off between interaction cost and matting quality. To balance performance and user-friendliness, we propose an improved deep image matting framework which is trimap-free and only needs sparse user click or scribble interaction to minimize the needed auxiliary constraints while still allowing interactivity. Moreover, we introduce uncertainty estimation that predicts which parts need polishing and conduct uncertainty-guided refinement. To trade off runtime against refinement quality, users can also choose different refinement modes. Experimental results show that our method performs better than existing trimap-free methods and comparably to state-of-the-art trimap-based methods with minimal user effort. Finally, we demonstrate the extensibility of our framework to video human matting without any structure modification, by adding optical flow-based sparse hint propagation and temporal consistency regularization imposed on the single frame.

Knockdown of BACE1 by a multistage brain-targeting polyion complex improved memory and learning behaviors in APP/PS1 transgenic mouse model.

Cleavage of Amyloid precursor protein (APP) by the ß-site amyloid precursor protein cleaving enzyme 1 (BACE1) is the rate-limiting step in the production of amyloid-ß (Aß) synaptotoxins. The siRNA-mediated silencing to attenuate the expression of BACE1 to ameliorate cognitive dysfunction in mice had been investigated. To improve therapeutic gene delivery to the central nervous system, cationic copolymer poly(ethylene glycol)-b-poly[N-(N'-{N''-[N'''-(2-aminoethyl)-2-aminoethyl]-2-aminoethyl}-2-aminoethyl)aspartamide]-cholesterol was synthesized, then RVG29 and Tet1 peptides were exploited as ligands to construct a dual-targeting brain gene delivery polyion complex (Tet1/RVG29-PIC). The cell uptake of a coculture cell model showed that the Tet1/RVG29-PIC exhibited notable transport characteristics and possessed affinity towards nerve cells. In vivo transfection, Tet1/RVG29-PIC possessed the highest expression of luciferase in brain compared with that of RVG29-PIC or Tet1-PIC, which were 1.25 and 1.22 times respectively. Silence BACE1 expression using siRNA-expressing plasmid loaded Tet1/RVG29-PIC that improved behavioral deficits in the APP/PS1 mouse model, demonstrating the favorable brain delivery properties of Tet1/RVG29-PIC by synergistical engagement of GT1B and nicotinic acetylcholine receptors. Our results suggested that the nanoformulation has the potential to be exploited as a multistage-targeting gene vector for the CNS disease therapy.

A micro-nano interface integrated SERS-based microfluidic sensor for miRNA detection using DNAzyme walker amplification.

BACKGROUND: Precise and specific miRNA detection plays a vital role in exploring development mechanisms of cancer disease, thereby it can significantly improve relevant prevention and treatment strategies. RESULTS: In this work, a surface-enhanced Raman spectroscopy (SERS)-based microfluidic chip has been devised with a microcone array SERS substrate (MCASS) for the miR-141 detection. This substrate excels in unique SERS activity and large surface area for DNA oligonucleotide modification. As the presence of miR-141, the DNAzyme walker induced cleavage reaction took place on the finely designed and prepared dual DNA conjugated SERS nanoprobes. The SERS nanoprobes can anchor on MCASS by the DNA hybridization that achieved an impressive detection limit in the femtomolar level. SIGNIFICANCE: With this integrated SERS-based microfluidic chip, we provided a miRNA detection strategy using DNAzyme walker amplification technology. It is believed that this strategy could be a powerful tool for miRNA detection and related cancer screening test.

Plasma IgG aggregates as biomarkers for multiple sclerosis.

We recently reported that multiple sclerosis (MS) plasma contains IgG aggregates and induces complement-dependent neuronal cytotoxicity (Zhou et al., 2023). Using ELISA, we report herein that plasma IgG levels in the aggregates can be used as biomarkers for MS. We enriched the IgG aggregates from samples of two cohorts (190 MS and 160 controls) by collecting flow-through after plasma binding to Protein A followed by detection of IgG subclass. We show that there are significantly higher levels of IgG1, IgG3, and total IgG antibodies in MS IgG aggregates, with an AUC >90%; higher levels of IgG1 distinguish secondary progressive MS from relapsing-remitting MS (AUC = 91%). Significantly, we provided the biological rationale for MS plasma IgG biomarkers by demonstrating the strong correlation between IgG antibodies and IgG aggregate-induced neuronal cytotoxicity. These non-invasive, simple IgG-based blood ELISA assays can be adapted into clinical practice for diagnosing MS and SPMS and monitoring treatment responses.

Preliminary study of noninvasive prenatal screening for 22q11.2 deletion/duplication syndrome using multiplex dPCR assay.

OBJECTIVE: This study aimed to establish a cell-free fetal DNA (cffDNA) assay using multiplex digital PCR (dPCR) for identifying fetuses at increased risk of 22q11.2 deletion/duplication syndrome. METHODS: Six detection sites and their corresponding probes were designed for the 22q11.2 recurrent region. A dPCR assay for the noninvasive screening of 22q11.2 deletion/duplication syndrome was established. A total of 130 plasma samples from pregnant women (including 15 samples with fetal 22q11.2 deletion/duplication syndrome) were blindly tested for evaluating the sensitivity and specificity of the established assay. RESULTS: DNA with different sizes of 22q11.2 deletion/duplication was detected via dPCR, indicating that the designed probes and detection sites were reasonable and effective. In the retrospective clinical samples, 11 out of 15 samples of pregnant women with 22q11.2 deletion/duplication were detected during the cffDNA assay, and accurate regional localization was achieved. Among the 115 normal samples, 111 were confirmed to be normal. Receiver operating characteristic curves were used for assessing the cut-off values and AUC for these samples. The sensitivity, specificity, and positive as well as negative predictive values were 73.3%, 96.5%, 73.3%, and 96.5%, respectively. CONCLUSION: The cffDNA assay based on dPCR technology for the noninvasive detection of 22q11.2 recurrent copy number variants in fetuses detected most affected cases, including smaller but relatively common nested deletions, with a low false-positive rate. It is a potential, efficient and simple method for the noninvasive screening of 22q11.2 deletion/duplication syndrome.

Synthesis and Application of Porous Carbon Nanomaterials from Pomelo Peels: A Review.

Advanced carbon nanomaterials have been widely applied in various fields such as microelectronics, energy storage, catalysis, adsorption, biomedical engineering, and material strengthening. With the increasing demand for porous carbon nanomaterials, many studies have explored obtaining porous carbon nanomaterials from biomass, which is highly abundant. Pomelo peel, a type of biomass rich in cellulose and lignin, has been widely upgraded into porous carbon nanomaterials with large yield and significant applications. Here, we systematically review the recent progress in pyrolysis, activation, and applications of synthesizing porous carbon nanomaterials from waste pomelo peels. Moreover, we provide a perspective on the remaining challenges and potential future research directions.

Characterization of metabolism-associated molecular patterns in prostate cancer.

BACKGROUND: Metabolism is a hallmark of cancer and it involves in resistance to antitumor treatment. Therefore, the purposes of this study are to classify metabolism-related molecular pattern and to explore the molecular and tumor microenvironment characteristics for prognosis predicting in prostate cancer. METHODS: The mRNA expression profiles and the corresponding clinical information for prostate cancer patients from TCGA, cBioPortal, and GEO databases. Samples were classified using unsupervised non-negative matrix factorization (NMF) clustering based on differentially expressed metabolism-related genes (MAGs). The characteristics of disease-free survival (DFS), clinicopathological characteristics, pathways, TME, immune cell infiltration, response to immunotherapy, and sensitivity to chemotherapy between subclusters were explored. A prognostic signature was constructed by LASSO cox regression analysis based on differentially expressed MAGs and followed by the development for prognostic prediction. RESULTS: A total of 76 MAGs between prostate cancer samples and non-tumorous samples were found, then 489 patients were divided into two metabolism-related subclusters for prostate cancer. The significant differences in clinical characteristics (age, T/N stage, Gleason) and DFS between two subclusters. Cluster 1 was associated with cell cycle and metabolism-related pathways, and epithelial-mesenchymal transition (EMT), etc., involved in cluster 2. Moreover, lower ESTIMATE/immune/stromal scores, lower expression of HLAs and immune checkpoint-related genes, and lower half-maximal inhibitory concentration (IC50) values in cluster 1 compared with cluster 2. The 10 MAG signature was identified and constructed a risk model for DFS predicting. The patients with high-risk scores showed poorer DFS. The area under the curve (AUC) values for 1-, 3-, 5-year DFS were 0.744, 0.731, 0.735 in TCGA-PRAD dataset, and 0.668, 0.712, 0.809 in GSE70768 dataset, 0.763, 0.802, 0.772 in GSE70769 dataset. Besides, risk score and Gleason score were identified as independent factors for DFS predicting, and the AUC values of risk score and Gleason score were respectively 0.743 and 0.738. The nomogram showed a favorable performance in DFS predicting. CONCLUSION: Our data identified two metabolism-related molecular subclusters for prostate cancer that were distinctly characterized in prostate cancer. Metabolism-related risk profiles were also constructed for prognostic prediction.

Platelet counts affect the association between hyperhomocysteinemia and pregnancy complications.

BACKGROUND: The joint effect of platelet and other modifiers on the risk of pregnancy complications is unknown. This study investigated whether platelet count (PC) and total homocysteine (tHcy) level have a synergistic effect on the incidence of pregnancy complications in a Chinese population. METHODS: Total 11,553 consecutive pregnant women who received whole blood cell and biochemical tests at the time of admission for labor in Changzhou Maternal and Child Health Care Hospital were analyzed. The primary outcome was the prevalence of pregnancy complications: gestational diabetes mellitus (GDM), intrahepatic cholestasis of pregnancy (ICP), pre-eclampsia (PE), and pregnancy induced hypertension (PIH). RESULTS: The prevalence of GDM, ICP, PE, and PIH was 8.4%, 6.2%, 3.4%, and 2.1%, respectively. The highest rate of ICP (28.6%) was observed in women with high tHcy (> 15 µmol/L) and low PC (quartile 1); and the lowest rate of GDM (0.6%) was found in women with high tHcy and high PC (quartiles 2 to 4). In low PC group, the prevalence of ICP in women with high tHcy was significantly higher than that in women with low tHcy (≤ 15 µmol/L) (28.6% vs. 8.4%), representing an absolute risk increment of 20.2% and a relative risk increment of 3.3-fold (OR: 3.34; 95% CI: 1.55, 7.17; P = 0.002), whereas no joint effect was observed among high PC group. CONCLUSIONS: Among Chinese pregnant women, one subgroup (high tHcy and low PC) has the highest risk of ICP and another (high tHcy and high PC) has the lowest risk of GDM; tHcy and platelet could be used as indicators to identify the women with high risk of ICP or low risk of GDM.

Preclinical characterization of WB737, a potent and selective STAT3 inhibitor, in natural killer/T-cell lymphoma.

Natural killer/T-cell lymphoma (NKTL) is an uncommon malignancy with poor prognosis and limited therapeutic options. Activating mutations of signal transducer and activator of transcription 3 (STAT3) are frequently found in patients with NKTL, suggesting that targeted inhibition of STAT3 is a potential therapeutic option for this disease. Here, we have developed a small molecule drug WB737 as a novel and potent STAT3 inhibitor that directly binds to the STAT3-Src homology 2 domain with high affinity. In addition, the binding affinity of WB737 to STAT3 is 250-fold higher than STAT1 and STAT2. Interestingly, WB737 is more selective for NKTL with STAT3-activating mutations in terms of growth inhibition and apoptotic induction when compared with Stattic. Mechanistically, WB737 inhibits both canonical and noncanonical STAT3 signaling via suppression of STAT3 phosphorylation at Tyr705 and Ser727, respectively, thereby inhibiting the expression of c-Myc and mitochondria-related genes. Moreover, WB737 inhibited STAT3 more potently than Stattic, resulting in a significant antitumor effect with undetectable toxicity, followed by almost complete tumor regression in an NKTL xenograft model harboring a STAT3-activating mutation. Taken together, these findings provide preclinical proof-of-concept for WB737 as a novel therapeutic strategy for the treatment of NKTL patients with STAT3-activating mutations.

A Robust Approach to Multimodal Deepfake Detection.

The widespread use of deep learning techniques for creating realistic synthetic media, commonly known as deepfakes, poses a significant threat to individuals, organizations, and society. As the malicious use of these data could lead to unpleasant situations, it is becoming crucial to distinguish between authentic and fake media. Nonetheless, though deepfake generation systems can create convincing images and audio, they may struggle to maintain consistency across different data modalities, such as producing a realistic video sequence where both visual frames and speech are fake and consistent one with the other. Moreover, these systems may not accurately reproduce semantic and timely accurate aspects. All these elements can be exploited to perform a robust detection of fake content. In this paper, we propose a novel approach for detecting deepfake video sequences by leveraging data multimodality. Our method extracts audio-visual features from the input video over time and analyzes them using time-aware neural networks. We exploit both the video and audio modalities to leverage the inconsistencies between and within them, enhancing the final detection performance. The peculiarity of the proposed method is that we never train on multimodal deepfake data, but on disjoint monomodal datasets which contain visual-only or audio-only deepfakes. This frees us from leveraging multimodal datasets during training, which is desirable given their lack in the literature. Moreover, at test time, it allows to evaluate the robustness of our proposed detector on unseen multimodal deepfakes. We test different fusion techniques between data modalities and investigate which one leads to more robust predictions by the developed detectors. Our results indicate that a multimodal approach is more effective than a monomodal one, even if trained on disjoint monomodal datasets.

Transformer-Based Detection for Highly Mobile Coded OFDM Systems.

This paper is concerned with mobile coded orthogonal frequency division multiplexing (OFDM) systems. In the high-speed railway wireless communication system, an equalizer or detector should be used to mitigate the intercarrier interference (ICI) and deliver the soft message to the decoder with the soft demapper. In this paper, a Transformer-based detector/demapper is proposed to improve the error performance of the mobile coded OFDM system. The soft modulated symbol probabilities are computed by the Transformer network, and are then used to calculate the mutual information to allocate the code rate. Then, the network computes the codeword soft bit probabilities, which are delivered to the classical belief propagation (BP) decoder. For comparison, a deep neural network (DNN)-based system is also presented. Numerical results show that the Transformer-based coded OFDM system outperforms both the DNN-based and the conventional system.

Impact of Maternal Monocyte to High-density Lipoprotein Cholesterol Ratio on the Incidence of Large-for-gestational-age Newborns: An Observational Cohort Study.

BACKGROUND AND OBJECTIVES: Monocyte to high-density lipoprotein cholesterol ratio (MHR) has recently been identified as a new marker of inflammation and oxidative stress. However, it is unknown whether maternal MHR is associated with fetal weight at birth. Therefore, our objective was to analyze the association between maternal MHR and the frequency of small/large for gestational age (SGA/LGA) newborns in this retrospective cohort study. METHODS: We retrospectively analyzed hospitalization records and laboratory data and obtained results from consecutive pregnant women in whom the blood lipid level had been investigated along with the blood cell count. Linear regression and logistic regression analyses were performed to estimate the associations of maternal MHR with birth weight and SGA/LGA. RESULTS: Monocyte counts and MHR were positively associated with birth weight/LGA risk (monocyte [1-109/L increase] for birth weight: ß: 170.24, 95% confidence interval [CI]: 41.72-298.76, LGA: odds ratio [OR]: 7.67; 95% CI: 2.56-22.98; MHR [1-109/mmol increase] for birth weight: ß: 294.84, 95% CI: 170.23-419.44, LGA: OR: 7.97; 95% CI: 3.06-20.70), whereas high-density lipoprotein cholesterol (HDL-C) levels were negatively associated with birth weight/LGA risk [1 mmol/L increase for birth weight (ß: -99.83, 95% CI: -130.47 to -69.19), for LGA: (OR: 0.57, 95% CI: 0.45-0.73). Obese pregnant women (body mass index [BMI] ≥30 kg/m2) with higher MHR (tertile 3: >0.33 109/mmol) significantly increased LGA risk by 6.39 fold (95% CI: 4.81, 8.49) compared to those with low MHR (tertile 1-2: ≤0.33 109/mmol) and normal weight (BMI <25 kg/m2). CONCLUSION: Maternal MHR is associated with LGA risk, and this association might be further modified by BMI.

Multiple sclerosis plasma IgG aggregates induce complement-dependent neuronal apoptosis.

Grey matter pathology is central to the progression of multiple sclerosis (MS). We discovered that MS plasma immunoglobulin G (IgG) antibodies, mainly IgG1, form large aggregates (>100 nm) which are retained in the flow-through after binding to Protein A. Utilizing an annexin V live-cell apoptosis detection assay, we demonstrated six times higher levels of neuronal apoptosis induced by MS plasma IgG aggregates (n = 190, from two cohorts) compared to other neurological disorders (n = 116) and healthy donors (n = 44). MS IgG aggregate-mediated, complement-dependent neuronal apoptosis was evaluated in multiple model systems including primary human neurons, primary human astrocytes, neuroblastoma SH-SY5Y cells, and newborn mouse brain slices. Immunocytochemistry revealed the co-deposition of IgG, early and late complement activation products (C1q, C3b, and membrane attack complex C5b9), as well as active caspase 3 in treated neuronal cells. Furthermore, we found that MS plasma cytotoxic antibodies are not present in Protein G flow-through, nor in the paired plasma. The neuronal apoptosis can be inhibited by IgG depletion, disruption of IgG aggregates, pan-caspase inhibitor, and is completely abolished by digestion with IgG-cleaving enzyme IdeS. Transmission electron microscopy and nanoparticle tracking analysis revealed the sizes of MS IgG aggregates are greater than 100 nm. Our data support the pathological role of MS IgG antibodies and corroborate their connection to complement activation and axonal damage, suggesting that apoptosis may be a mechanism of neurodegeneration in MS.