PyHFO: lightweight deep learning-powered end-to-end high-frequency oscillations analysis application.

OBJECTIVE: This study aims to develop and validate an end-to-end software platform, PyHFO, that streamlines the application of deep learning methodologies in detecting neurophysiological biomarkers for epileptogenic zones from EEG recordings. Methods: We introduced PyHFO, which enables time-efficient HFO detection algorithms like short-term energy (STE) and Montreal Neurological Institute and Hospital (MNI) detectors. It incorporates deep learning models for artifact and HFO with spike classification, designed to operate efficiently on standard computer hardware. Main results: The validation of PyHFO was conducted on three separate datasets: the first comprised solely of grid/strip electrodes, the second a combination of grid/strip and depth electrodes, and the third derived from rodent studies, which sampled the neocortex and hippocampus using depth electrodes. PyHFO demonstrated an ability to handle datasets efficiently, with optimization techniques enabling it to achieve speeds up to 50 times faster than traditional HFO detection applications. Users have the flexibility to employ our pre-trained deep learning model or use their EEG data for custom model training. Significance: PyHFO successfully bridges the computational challenge faced in applying deep learning techniques to EEG data analysis in epilepsy studies, presenting a feasible solution for both clinical and research settings. By offering a user-friendly and computationally efficient platform, PyHFO paves the way for broader adoption of advanced EEG data analysis tools in clinical practice and fosters potential for large-scale research collaborations.

Targeting PCSK9 to upregulate MHC-II on the surface of tumor cells in tumor immunotherapy.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9), the last member of the proprotein convertase family, functions as a classic regulator of low-density lipoprotein (LDL) by interacting with low-density lipoprotein receptor (LDLR). Recent studies have shown that PCSK9 can affect the occurrence and development of tumors and can be used as a novel therapeutic target. However, a comprehensive pan-cancer analysis of PCSK9 has yet to be conducted. METHODS: The potential oncogenic effects of PCSK9 in 33 types of tumors were explored based on the datasets of The Cancer Genome Atlas (TCGA) dataset. In addition, the immune regulatory role of PCSK9 inhibition was evaluated via in vitro cell coculture and the tumor-bearing mouse model. Finally, the antitumor efficacy of targeted PCSK9 combined with OVA-II vaccines was verified. RESULTS: Our results indicated that PCSK9 was highly expressed in most tumor types and was significantly correlated with late disease stage and poor prognosis. Additionally, PCSK9 may regulate the tumor immune matrix score, immune cell infiltration, immune checkpoint expression, and major histocompatibility complex expression. Notably, we first found that dendritic cell (DC) infiltration and major histocompatibility complex-II (MHC-II) expression could be upregulated by PCSK9 inhibition and improve CD8+ T cell activation in the tumor immune microenvironment, thereby achieving potent tumor control. Combining PCSK9 inhibitors could enhance the efficacies of OVA-II tumor vaccine monotherapy. CONCLUSIONS: Conclusively, our pan-cancer analysis provided a more comprehensive understanding of the oncogenic and immunoregulatory roles of PCSK9 and demonstrated that targeting PCSK9 could increase the efficacy of long peptide vaccines by upregulating DC infiltration and MHC-II expression on the surface of tumor cells. This study reveals the critical oncogenic and immunoregulatory roles of PCSK9 in various tumors and shows the promise of PCSK9 as a potent immunotherapy target.

Molecular and Supramolecular Materials: From Light-Harvesting to Quantum Information Science and Technology.

The past two decades have witnessed immense advances in quantum information technology (QIT), benefited by advances in physics, chemistry, biology, and materials science and engineering. It is intriguing to consider whether these diverse molecular and supramolecular structures and materials, partially inspired by quantum effects as observed in sophisticated biological systems such as light-harvesting complexes in photosynthesis and the magnetic compass of migratory birds, might play a role in future QIT. If so, how? Herein, we review materials and specify the relationship between structures and quantum properties, and we identify the challenges and limitations that have restricted the intersection of QIT and chemical materials. Examples are broken down into two categories: materials for quantum sensing where nonclassical function is observed on the molecular scale and systems where nonclassical phenomena are present due to intermolecular interactions. We discuss challenges for materials chemistry and make comparisons to related systems found in nature. We conclude that if chemical materials become relevant for QIT, they will enable quite new kinds of properties and functions.

Bacteria-mediated resistance of neutrophil extracellular traps to enzymatic degradation drives the formation of dental calculi.

Dental calculi can cause gingival bleeding and periodontitis, yet the mechanism underlying the formation of such mineral build-ups, and in particular the role of the local microenvironment, are unclear. Here we show that the formation of dental calculi involves bacteria in local mature biofilms converting the DNA in neutrophil extracellular traps (NETs) from being degradable by the enzyme DNase I to being degradation resistant, promoting the nucleation and growth of apatite. DNase I inhibited NET-induced mineralization in vitro and ex vivo, yet plasma DNases were ineffective at inhibiting ectopic mineralization in the oral cavity in rodents. The topical application of the DNA-intercalating agent chloroquine in rodents fed with a dental calculogenic diet reverted NET DNA to its degradable form, inhibiting the formation of calculi. Our findings may motivate therapeutic strategies for the reduction of the prevalence of the deposition of bacteria-driven calculi in the oral cavity.

Assessment of the association between D-dimer levels and clinicopathological characteristics of pancreatic cancer and its role in prognosis: A systematic review and meta-analysis.

According to previous studies, D-dimer levels are associated with the prognosis of patients with pancreatic cancer (PC). However, the results of current studies are limited and controversial. Therefore, we performed this meta-analysis to assess the relationship between D-dimer levels and prognostic and pathological characteristics of PC patients. We first searched the databases of PubMed, Embase, The Cochrane Library, Web Of Science, CBM, VIP, CNKI and Wanfang to identify available studies. The relationship between pretreatment d-dimer levels and prognosis in PC patients was assessed using the combined hazard ratio (HR) and 95% confidence interval (CI). The combined odds ratio (OR) and 95% confidence interval (CI) were used in assessing the relationship between pathological characteristics and d-dimer levels in PC patients. Stata 12.0 software was used for all statistical analyses. In total, we included 13 studies involving 2777 patients. The results showed that elevated pre-treatment d -dimer levels were significantly associated with OS deterioration (HR = 1.46 95% CI: 1.34-1.59; p < 0.001). We also performed subgroup analyses based on sample size, d -dimer threshold, follow-up time, and HR source to further validate the prognostic value of pretreatment d -dimer levels in PC. In addition, according to the analysis, high pretreatment d -dimer levels in PC patients were associated with late tumor stage (OR = 4.78, 95% CI 1.73-13.20, p < 0. 005), larger tumor size (OR = 1.72, 95% CI 1.25-2.35, p < 0.005), and distant metastasis of tumor (OR = 5.06, 95% CI 2.45-10.43, p < 0.005) were significantly associated. In contrast, other clinicopathological factors, including age, gender and lymph node metastasis, were not associated with d-dimer levels. In conclusion, we found that high pre-treatment d-dimer levels were associated with a poor prognosis in PC patients, in relation to later tumor stage, larger tumor size and the development of distant metastases. Plasma d-dimer levels can be used as a biomarker of prognosis in PC patients.

The association between tinnitus and risk of cardiovascular events and all-cause mortality: insight from the UK Biobank.

BACKGROUND: The potential influence of tinnitus on cardiovascular disease (CVD) and all-cause mortality has yet to be explored. We aim to examine the correlations between tinnitus and the risk of cardiovascular events and all-cause mortality. METHODS: We conducted a prospective cohort study utilising data from the UK Biobank. The presence of tinnitus was evaluated through a questionnaire. The primary outcome was defined as a composition of cardiovascular events, including myocardial infarction (MI), stroke, and mortality from CVD, as well as all-cause mortality. Cox proportional hazard models were employed to examine the associations between tinnitus and both the primary outcome and its individual components. Sensitivity analyses were conducted to evaluate the robustness of the primary analysis. RESULTS: A total of 140,146 participants were included in the study. The presence of tinnitus was found to be associated with a higher incident rate of the primary outcome (HR = 1.057, 95%CI: 1.017-1.099, p = 0.005), MI (HR = 1.139, 95%CI: 1.061-1.222, p < 0.001) and all-cause mortality (HR = 1.053, 95%CI: 1.003-1.105, p = 0.038) after adjusting for confounders. However, there was no significant association between tinnitus and stroke or mortality from CVD. Subgroup analysis revealed that the association between tinnitus and the primary outcome was significant in females, participants with abnormal BMI, and those without hearing difficulty, depression or anxiety. Sensitivity analyses yielded consistent results. CONCLUSION: The findings from this study contribute to the existing body of evidence suggesting an association between tinnitus and an increased risk of cardiovascular events and all-cause mortality.

Association between immune-related hub genes CD36, CXCL13, FGFR4, GABBR1, LAMP3, MMP12, and PPM1H and colorectal cancer prognosis.

The present study aims to identify immune-related prognostic genes in colorectal cancer (CRC), and to explore potential mechanisms through which these genes regulate CRC progression. We first constructed a prognostic risk model based on seven gene signatures [cluster of differentiation-36 (CD36), chemokine (C-X-C-motif) ligand 13 (CXCL13), fibroblast growth factor receptor 4 (FGFR4), gamma-amino-butyric acid type B receptor 1 (GABBR1), lysosome-associated membrane glycoprotein 3 (LAMP3), recombinant matrix metalloproteinase 12 (MMP12), and protein phosphatase 1H (PPM1H)] using integrated bioinformatic analyses. FGFR4, GABBR1, and LAMP3 were highly expressed in CRC cell lines (in comparison with a normal colonic epithelial cell line), while CD36, CXCL13, MMP12, and PPM1H were weakly expressed. These in vitro expression results were largely consistent with our bioinformatic analysis. A prognostic model was generated to identify a high-risk group with worse survival outcome based on Kaplan-Meier analysis. Our prognostic model showed superior accuracy in both the training and test cohorts. In addition, we found that the low-risk subgroup exhibited greater infiltration by M1 macrophages, CD8+ T cells, CD4+ T cells, and activated NK cells. In conclusion, our findings provide evidence that seven immune-related hub genes can be considered as gene signatures to predict CRC prognosis and to differentiate CRC patient benefit, ultimately serving as a guide for individualized immunotherapy.

Efficient production of 1,2,4-butanetriol from corn cob hydrolysate by metabolically engineered Escherichia coli.

Corn cob is a major waste mass-produced in corn agriculture. Corn cob hydrolysate containing xylose, arabinose, and glucose is the hydrolysis product of corn cob. Herein, a recombinant Escherichia coli strain BT-10 was constructed to transform corn cob hydrolysate into 1,2,4-butanetriol, a platform substance with diversified applications. To eliminate catabolite repression and enhance NADPH supply for alcohol dehydrogenase YqhD catalyzed 1,2,4-butanetriol generation, ptsG encoding glucose transporter EIICBGlc and pgi encoding phosphoglucose isomerase were deleted. With four heterologous enzymes including xylose dehydrogenase, xylonolactonase, xylonate dehydratase, α-ketoacid decarboxylase and endogenous YqhD, E. coli BT-10 can produce 36.63 g/L 1,2,4-butanetriol with a productivity of 1.14 g/[L·h] using xylose as substrate. When corn cob hydrolysate was used as the substrate, 43.4 g/L 1,2,4-butanetriol was generated with a productivity of 1.09 g/[L·h] and a yield of 0.9 mol/mol. With its desirable characteristics, E. coli BT-10 is a promising strain for commercial 1,2,4-butanetriol production.

Adaptive Internal Model Control for a Flexible Wing With Unsteady Aerodynamic Loads.

This article proposes adaptive internal model controls for the collocated output regulation of a flexible wing, where distributed disturbances, boundary disturbances, and references are from an exactly unknown exosystem. Observer-based tracking error feedback controls are first designed to address the robust output regulation in case of a known exosystem matrix. If the exosystem has an unknown matrix, an adaptive observer is further proposed with the observer error system converging to zero exponentially. Then, we can obtain adaptive observer-based controls by combining adaptive observers and observer-based controls, which are able to regulate the tracking errors toward zero in case of the exactly unknown disturbances and references. The corresponding closed-loop system is proved to be internally asymptotically stable. A simulation example is further provided for adaptive internal model control of the wing system.

Kinetic and Thermodynamic Control of Supramolecular Aggregation of Near Infrared Pyrrolopyrrole Cyanine Fluorophores Confined in Colloidal Nanoparticles.

Control of the intermolecular aggregation of organic π-conjugated molecules as chromophores is crucial for tuning their physical properties such as light absorption/emission, and energy and charge transfer. Lots of advances have been achieved in control of intermolecular aggregation of organic chromophores in solid states where an indefinitely large number of molecules are involved. However, much less understanding has been gained at a mesoscale of aggregates formed by well-defined organization of a deterministic number of chromophores, which has been realized in natural photosynthetic systems but still remains rare in manmade materials. Here, we report both the kinetic and the thermodynamic control of the supramolecular aggregation of a near-infrared cyanine dye, PPcy, and its derivatives confined in colloidal nanoparticles stabilized by surfactants in aqueous media. Our results demonstrate that both the aggregation number, the aggregation state and the optical properties of the PPcy chromophores are controllable through optimization of the alkyl and polymer chains tethered from PPcy, the effective concentration of the chromophore inside each particle, and the surfactants utilized to stabilize the colloids in water.

Structure-Unit-Based Total Synthesis of (-)-Sinulochmodin C.

Herein we report a structure-unit-based asymmetric total synthesis of sinulochmodin C, a norcembranoid diterpenoid bearing a transannular strained ether bridge ß-keto tetrahydrofuran moiety. Our synthetic route features an intramolecular double Michael addition to construct stereospecifically the [7,6,5,5] tetracyclic skeleton, a vinylogous hydroxylation/oxidation procedure or a stereospecific epoxide opening/oxidation sequence to establish the γ-keto enone intermediate, a Lewis acid/Brønsted acid mediated transannular oxa-Michael addition to fuse the ß-keto tetrahydrofuran moiety, a Mukaiyama hydration/Pd-C hydrogenation to reverse the C1-configuration of the isopropenyl unit, and a bioinspired transformation of sinulochmodin C into scabrolide A.

Advancing remote consultation through the integration of blockchain and ant colony algorithm.

To guide the more reasonable and fair allocation of medical resources, to solve the problem of fee prices negotiated by various subjects in the medical and health system and patient payment, and to solve the problem of how to ensure the privacy, accuracy, consistency and traceability of data in the process of collecting patient information in each hospital, according to the operation process of a remote consultation service, a decentralized remote intelligent consultation blockchain model is proposed. The model uses the improved ant colony algorithm under a smart contract and studies the practicality of the improved ant colony algorithm on the multi-node remote consultation service simulation platform. According to the experimental analysis results, the improved ant colony algorithm can automatically execute and effectively match the target population under the smart contract.

A telomere-to-telomere reference genome provides genetic insight into the pentacyclic triterpenoid biosynthesis in Chaenomeles speciosa.

Chaenomeles speciosa (2n = 34), a medicinal and edible plant in the Rosaceae, is commonly used in traditional Chinese medicine. To date, the lack of genomic sequence and genetic studies has impeded efforts to improve its medicinal value. Herein, we report the use of an integrative approach involving PacBio HiFi (third-generation) sequencing and Hi-C scaffolding to assemble a high-quality telomere-to-telomere genome of C. speciosa. The genome comprised 650.4 Mb with a contig N50 of 35.5 Mb. Of these, 632.3 Mb were anchored to 17 pseudo-chromosomes, in which 12, 4, and 1 pseudo-chromosomes were represented by a single contig, two contigs, and four contigs, respectively. Eleven pseudo-chromosomes had telomere repeats at both ends, and four had telomere repeats at a single end. Repetitive sequences accounted for 49.5% of the genome, while a total of 45 515 protein-coding genes have been annotated. The genome size of C. speciosa was relatively similar to that of Malus domestica. Expanded or contracted gene families were identified and investigated for their association with different plant metabolisms or biological processes. In particular, functional annotation characterized gene families that were associated with the biosynthetic pathway of oleanolic and ursolic acids, two abundant pentacyclic triterpenoids in the fruits of C. speciosa. Taken together, this telomere-to-telomere and chromosome-level genome of C. speciosa not only provides a valuable resource to enhance understanding of the biosynthesis of medicinal compounds in tissues, but also promotes understanding of the evolution of the Rosaceae.

Elaboration and validation of a prognostic signature associated with disulfidoptosis in lung adenocarcinoma, consolidated with integration of single-cell RNA sequencing and bulk RNA sequencing techniques.

Background: Lung adenocarcinoma (LUAD), the predominant subtype of non-small cell lung cancer (NSCLC), remains a pervasive global public health concern. Disulfidoptosis, a nascent form of regulated cell death (RCD), presents an emerging field of inquiry. Currently, investigations into disulfidoptosis are in their initial stages. Our undertaking sought to integrate single-cell RNA sequencing (scRNA-seq) in conjunction with traditional bulk RNA sequencing (bulk RNA-seq) methodologies, with the objective of delineating genes associated with disulfidoptosis and subsequently prognosticating the clinical outcomes of LUAD patients. Methods: Initially, we conducted an in-depth examination of the cellular composition disparities existing between LUAD and normal samples using scRNA-seq data sourced from GSE149655. Simultaneously, we scrutinized the expression patterns of disulfidoptosis-associated gene sets across diverse cell types. Subsequently, leveraging the bulk RNA-seq data, we formulated disulfidoptosis-related prognostic risk signatures (DRPS) employing LASSO-Cox regression. This was accomplished by focusing on genes implicated in disulfidoptosis that exhibited differential expression within endothelial cells (ECs). Sequentially, the robustness and precision of the DRPS model were rigorously verified through both internal and external validation datasets. In parallel, we executed single-cell trajectory analysis to delve into the differentiation dynamics of ECs. Concluding our study, we undertook a comprehensive investigation encompassing various facets. These included comparative assessments of enrichment pathways, clinicopathological parameters, immune cell abundance, immune response-associated genes, impacts of immunotherapy, and drug predictions among distinct risk cohorts. Results: The scrutiny of scRNA-seq data underscored discernible disparities in cellular composition between LUAD and normal samples. Furthermore, disulfidoptosis-associated genes exhibited marked discrepancies within endothelial cells (ECs). Consequently, we formulated the Disulfidoptosis-Related Prognostic Signature (DRPS) to facilitate prognostic prediction. The prognostic nomogram based on the risk score effectively demonstrated DRPS's robust capacity to prognosticate survival outcomes. This assertion was corroborated by rigorous assessments utilizing both internal and external validation sets, thus affirming the commendable predictive accuracy and enduring stability of DRPS. Functional enrichment analysis shed light on the significant correlation of DRPS with pathways intrinsic to the cell cycle. Subsequent analysis unveiled correlations between DRPS and gene mutations characteristic of LUAD, as well as indications of an immunosuppressive status. Through drug prediction, we explored potential therapeutic agents for low-risk patients. Concluding our investigation, qRT-PCR experiments confirmed the heightened expression levels of EPHX1, LDHA, SHC1, MYO6, and TLE1 in lung cancer cell lines.

Optimizing detection and deep learning-based classification of pathological high-frequency oscillations in epilepsy.

OBJECTIVE: This study aimed to explore sensitive detection methods for pathological high-frequency oscillations (HFOs) to improve seizure outcomes in epilepsy surgery. METHODS: We analyzed interictal HFOs (80-500 Hz) in 15 children with medication-resistant focal epilepsy who underwent chronic intracranial electroencephalogram via subdural grids. The HFOs were assessed using the short-term energy (STE) and Montreal Neurological Institute (MNI) detectors and examined for spike association and time-frequency plot characteristics. A deep learning (DL)-based classification was applied to purify pathological HFOs. Postoperative seizure outcomes were correlated with HFO-resection ratios to determine the optimal HFO detection method. RESULTS: The MNI detector identified a higher percentage of pathological HFOs than the STE detector, but some pathological HFOs were detected only by the STE detector. HFOs detected by both detectors had the highest spike association rate. The Union detector, which detects HFOs identified by either the MNI or STE detector, outperformed other detectors in predicting postoperative seizure outcomes using HFO-resection ratios before and after DL-based purification. CONCLUSIONS: HFOs detected by standard automated detectors displayed different signal and morphological characteristics. DL-based classification effectively purified pathological HFOs. SIGNIFICANCE: Enhancing the detection and classification methods of HFOs will improve their utility in predicting postoperative seizure outcomes.

Cultivation of Spirulina platensis for nutrient removal from piggery wastewater.

The discharge of livestock wastewater without appropriate treatment causes severe harm to the environment and human health. In the pursuit of finding solutions to this problem, the cultivation of microalgae as feedstock for biodiesel and animal feed additive using livestock wastewater coupled with the removal of nutrients from wastewater has become a hot research topic. In this study, the cultivation of Spirulina platensis using piggery wastewater for the production of biomass and the removal of nutrients were studied. The results of single factor experiments confirmed that Cu2+ seriously inhibit the growth of Spirulina platensis, while the influences of nitrogen, phosphorous, and zinc on the growth of Spirulina platensis can all be described as "low promotes high inhibits." Spirulina platensis grew well in the 4-fold dilution of piggery wastewater supplemented with moderate sodium bicarbonate, which indicated that it is the limiting nutrients for Spirulina platensis growth in piggery wastewater. The biomass concentration of Spirulina platensis reached 0.56 g/L after 8 days of culture at the optimal conditions proposed by the response surface method, which were as follows: 4-fold dilution of piggery wastewater, 7 g/L sodium bicarbonate, pH of 10.5, initial OD560 of 0.63, light intensity of 3030 lx, and light time/dark time of 16 h/8 h. Spirulina platensis cultured in the diluted piggery wastewater contained 43.89% protein, 9.4% crude lipid, 6.41 mg/g chlorophyll a, 4.18% total sugar, 27.7 mg/kg Cu, and 246.2 mg/kg Zn. The removal efficiency for TN, TP, COD, Zn, and Cu from the wastewater by Spirulina platensis was 76%, 72%, 93.1%, 93.5%, and 82.5%, respectively. These results demonstrated the feasibility of piggery wastewater treatment by the cultivation of Spirulina platensis.

Influence of a Multiple Epoxy Chain Extender on the Rheological Behavior, Crystallization, and Mechanical Properties of Polyglycolic Acid.

This study investigated the impact of a multiple epoxy chain extender (ADR) on the rheological behavior, crystallization, and mechanical properties of polyglycolic acid (PGA). Tests of the torque and melt mass flow rate and dynamic rheological analysis were conducted to study the rheological behavior of PGA modified with ADR. The rheological results of the modified PGA showed a significantly increased viscosity and storage modulus with an increase in the ADR amount, which could be attributed to the chain extension/branching reactions between PGA and ADR. It was proved that ADR could be used as an efficient chain extender for tailoring the rheological performance of PGA. The Han plot of the modified PGA showed a transition of viscous behavior to elastic behavior, while the ADR content was increased from 0 to 0.9 phr. The formation of long-chain branches (LCBs) was confirmed via the Cole-Cole plot and weighted relaxation spectrum, wherein the LCBs substantially changed the rheological behavior of the modified PGA. The vGP plots predicted a star-type topological structure for the LCBs. The results of non-isothermal crystallization kinetics suggested that the crystallization of the modified PGA was predominantly homogeneous nucleation and three-dimensional growth. The crystallinity decreased slightly with the increase in the ADR amount. Compared to neat PGA, the modified PGA samples exhibited better tensile and flexural performances.