Congenital heart disease detection by pediatric electrocardiogram based deep learning integrated with human concepts.

Early detection is critical to achieving improved treatment outcomes for child patients with congenital heart diseases (CHDs). Therefore, developing effective CHD detection techniques using low-cost and non-invasive pediatric electrocardiogram are highly desirable. We propose a deep learning approach for CHD detection, CHDdECG, which automatically extracts features from pediatric electrocardiogram and wavelet transformation characteristics, and integrates them with key human-concept features. Developed on 65,869 cases, CHDdECG achieved ROC-AUC of 0.915 and specificity of 0.881 on a real-world test set covering 12,000 cases. Additionally, on two external test sets with 7137 and 8121 cases, the overall ROC-AUC were 0.917 and 0.907 while specificities were 0.937 and 0.907. Notably, CHDdECG surpassed cardiologists in CHD detection performance comparison, and feature importance scores suggested greater influence of automatically extracted electrocardiogram features on CHD detection compared with human-concept features, implying that CHDdECG may grasp some knowledge beyond human cognition. Our study directly impacts CHD detection with pediatric electrocardiogram and demonstrates the potential of pediatric electrocardiogram for broader benefits.

A cardiologist-like computer-aided interpretation framework to improve arrhythmia diagnosis from imbalanced training datasets.

Arrhythmias can pose a significant threat to cardiac health, potentially leading to serious consequences such as stroke, heart failure, cardiac arrest, shock, and sudden death. In computer-aided electrocardiogram interpretation systems, the inclusion of certain classes of arrhythmias, which we term "aggressive" or "bullying," can lead to the underdiagnosis of other "vulnerable" classes. To address this issue, a method for arrhythmia diagnosis is proposed in this study. This method combines morphological-characteristic-based waveform clustering with Bayesian theory, drawing inspiration from the diagnostic reasoning of experienced cardiologists. The proposed method achieved optimal performance in macro-recall and macro-precision through hyperparameter optimization, including spliced heartbeats and clusters. In addition, with increasing bullying by aggressive arrhythmias, our model obtained the highest average recall and the lowest average drop in recall on the nine vulnerable arrhythmias. Furthermore, the maximum cluster characteristics were found to be consistent with established arrhythmia diagnostic criteria, lending interpretability to the proposed method.

Amyloid-like aggregates of short self-assembly peptide selectively induce melanoma cell apoptosis.

With the rising global incidence of melanoma, new anti-melanoma drugs with low-inducing drug resistance and high selectivity are in urgent need. Inspired by the physiological events in which fibrillar aggregates formed by amyloid proteins are toxic to normal tissues, we here rationally design a tyrosinase responsive peptide, I4K2Y* (Ac-IIIIKKDopa-NH2). Such peptide self-assembled into long nanofibers outside the cells, while it was catalyzed into amyloid-like aggregates by tyrosinase which was rich in melanoma cells. The newly formed aggregates concentrated around the nucleus of melanoma cells, blocking the exchange of biomolecules between the nucleus and cytoplasm and finally leading to cell apoptosis via the S phase arrest in cell cycle distribution and dysfunction of mitochondria. Furthermore, I4K2Y* effectively inhibited B16 melanoma growth in a mouse model but with minimal side effects. We believe that the strategy of combining the usage of toxic amyloid-like aggregates and in-situ enzymatic reactions by specific enzymes in tumor cells will bring profound implications for designing new anti-tumor drugs with high selectivity.

A proposed artificial intelligence workflow to address application challenges leveraged on algorithm uncertainty.

Artificial Intelligence (AI) has achieved state-of-the-art performance in medical imaging. However, most algorithms focused exclusively on improving the accuracy of classification while neglecting the major challenges in a real-world application. The opacity of algorithms prevents users from knowing when the algorithms might fail. And the natural gap between training datasets and the in-reality data may lead to unexpected AI system malfunction. Knowing the underlying uncertainty is essential for improving system reliability. Therefore, we developed a COVID-19 AI system, utilizing a Bayesian neural network to calculate uncertainties in classification and reliability intervals of datasets. Validated with four multi-region datasets simulating different scenarios, our approach was proved to be effective to suggest the system failing possibility and give the decision power to human experts in time. Leveraging on the complementary strengths of AI and health professionals, our present method has the potential to improve the practicability of AI systems in clinical application.

Rapid Hemostasis Resulting from the Synergism of Self-Assembling Short Peptide and O-Carboxymethyl Chitosan.

The development of novel hemostatic agents with distinct modes of action from traditional ones remains a formidable challenge. Self-assembling peptide hydrogels have emerged as a new hemostatic material, not only because of their inherent biocompatibility and biodegradability but also their designability. Especially, rational molecular design can make peptides and their hydrogelation responsive to biological cues. In this study, we demonstrated that transglutaminase-catalyzed reactions not only occurred among designed short peptide I3QGK molecules but also between the peptide and a natural polysaccharide O-carboxymethyl chitosan. Because Factor XIII in the blood can rapidly convert into activated transglutaminase (Factor XIIIa) upon bleeding, these enzymatic reactions, together with the electrostatic attraction between the two hemostatic agents, induced a strong synergetic effect in promoting hydrogelation, blood coagulation, and platelet adhesion, eventually leading to rapid hemostasis. The study presents a promising strategy for developing alternative hemostatic materials and methods.

Total alkaloids of Sophora alopecuroides L. ameliorated murine colitis by regulating bile acid metabolism and gut microbiota.

ETHNOPHARMACOLOGICAL RELEVANCE: Sophora alopecuroides L. is one of the most commonly used plants in traditional medicine for the management conditions including inflammatory and gastrointestinal disease. However, the therapeutic mechanism of Sophora alopecuroides L.particularly in inflammatory bowel disease (IBD) remains unclear. AIM OF THE STUDY: To evaluate the treatment effects of total alkaloids of Sophora alopecuroides L. in ulcerative colitis (UC) mice model and explore the therapeutic mechanism of KDZ on UC based on bile acid metabolism and gut microbiota. MATERIALS AND METHODS: Colitis were induced in BALB/c mice by administering 3.5% dextran sulfate sodium (DSS) in drinking water for 7 days. The mice were then given KDZ (300, 150 and 75 mg/kg) and the positive drug sulfasalazine (SASP, 450 mg/kg) via oral administration for 7 days. The levels of 23 bile acids in the liver, bile, serum, cecum content and colon were determined through ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS). The cecum microbiota was characterized through high-throughput Illumina MiSeq sequencing. RESULTS: KDZ treatment significantly decreased the disease activity index (DAI) scores and ameliorated colonic injury in DSS-treated mice. The expression of IL-1ß and TGF-ß1 were suppressed, yet, IL-10 was up-regulated by KDZ and SASP treatment compared with those in the model group. Meanwhile, the serum contents of total bile acid and total cholesterol in the DSS group increased significantly compared with those in the control group, but reversed by SASP and KDZ. The relative abundance of Firmicutes increased after KDZ was administration, whereas the abundance of Bacteroidetes decreased. αMCA, ßMCA, ωMCA and CA in the SASP and KDZ groups did not differ from those in the control group, whereas these parameters significantly increased in the DSS group. CONCLUSIONS: KDZ had a protective effect on DSS-induced colitis by mitigating colonic injury, preventing gut microbiota dysbiosis and regulating bile acid metabolism.

Pulsatilla Decoction Can Treat the Dampness-Heat Diarrhea Rat Model by Regulating Glycerinphospholipid Metabolism Based Lipidomics Approach.

ETHNOPHARMACOLOGICAL RELEVANCE: Diarrhea is a major medical problem in clinical practice. According to the theory of traditional Chinese medicine (TCM), different types of diarrhea should be treated with different TCM formulations based on the targeted medical condition. Dampness-heat diarrhea (DHD) is a serious diarrheal disease and Pulsatilla decoction (PD), a TCM, has been found effective against DHD. OBJECTIVE: The aim of this study was to clarify the mechanism of action of PD in DHD using an untargeted lipidomics strategy. MATERIALS AND METHODS: Wistar rats were randomized to four groups, including the control group, model group, PD groups and self-healing group. The PD groups were given a daily intragastric gavage of PD at doses of 3.76 g/kg. The rat model of DHD established by such complex factors as high-sugar and high-fat diet, improper diet, high temperature and humidity environment, drinking and intraperitoneal injection of Escherichia coli., which imitated the inducing conditions of DHD. Then the clinical symptoms and signs, blood routine, serum inflammatory cytokines levels and the histopathological changes of main organs were detected and observed to evaluate DHD model and therapeutic effect of PD. Lipid biomarkers of DHD were selected by comparing the control and model groups with the colon lipidomics technology and an ultra-high performance liquid chromatography (UHPLC) coupled with Q Exactive plus mass analyzer. Multivariate statistical analysis and pattern recognition were employed to examine different lipids within the colon of PD-treated rats. RESULTS: The clinical symptoms and signs of the model rats were consistent with the diagnostic criteria of DHD. After treatment with PD, the clinical symptoms and signs of the rats with DHD were improved; the indexes of blood routine and inflammatory cytokines levels tended to be normal. The lipidomics profile of the model group were evidently disordered when compared to the control group. A total of 42 significantly altered lipids between the model-control groups were identified by multivariate statistical analysis. DHD may result from such lipid disorders which are related to glycerophospholipid metabolism, arachidonic acid (AA) metabolism, and sphingolipid metabolism. After PD treatment, the lipidomic profiles of the disorders tended to recover when compared to the model group. Twenty lipid molecules were identified and some glycerophospholipids and AA levels returned close to the normal level. CONCLUSION: Glycerophospholipid metabolism may play an important role in the treatment of dampness-heat induced diarrhea using PD.

Effects of Conventional Surfactants on the Activity of Designed Antimicrobial Peptide.

In this article, the interaction between a designed antimicrobial peptide (AMP) G(IIKK)3I-NH2 (G3) and four typical conventional surfactants (sodium dodecyl sulfonate (SDS), hexadecyl trimethyl ammonium bromide (C16TAB), polyoxyethylene (23) lauryl ether (C12EO23), and tetradecyldimethylamine oxide (C14DMAO)) has been studied through surface tension measurement and circular dichroism (CD) spectroscopy. The antimicrobial activities of AMP/surfactant mixtures have also been studied with Gram-negative Escherichia coli, Gram-positive Staphylococcus aureus, and the fungus Candida albicans. The cytotoxicity of the AMP/surfactant mixtures has also been assessed with NIH 3T3 and human skin fibroblast (HSF) cells. The surface tension data showed that the AMP/SDS mixture was much more surface-active than SDS alone. CD results showed that G3 conformation changed from random coil, to ß-sheet, and then to α-helix with increasing SDS concentration, showing a range of structural transformation driven by the different interactions with SDS. The antimicrobial activity of G3 to Gram-negative and Gram-positive bacteria decreased in the presence of SDS due to the strong interaction of electrostatic attraction between the peptide and the surfactant. The interactions between G3 and C16TAB, C12EO23, and C14DMAO were much weaker than SDS. As a result, the surface tension of surfactants with G3 did not change much, neither did the secondary structures of G3. The antimicrobial activities of G3 were little affected in the presence of C12EO23, slightly improved by C14DMAO, and clearly enhanced by cationic surfactant C16TAB due to its strong cationic and antimicrobial nature, consistent with their surface physical activities as binary mixtures. Although AMP G3 did not show activity to fungus, the mixtures of AMP/C16TAB and AMP/C14DMAO could kill C. albicans at high surfactant concentrations. The mixtures had rather high cytotoxicity to NIH 3T3 and HSF cells although G3 is nontoxic to cells. Cationic AMPs can be formulated with nonionic, cationic, and zwitterionic surfactants during product development, but care must be taken when AMPs are formulated with anionic surfactants, as the strong electrostatic interaction may undermine their antimicrobial activity.

Modulation of Antimicrobial Peptide Conformation and Aggregation by Terminal Lipidation and Surfactants.

The function and properties of peptide-based materials depend not only on the amino acid sequence but also on the molecular conformations. In this paper, we chose a series of peptides Gm(XXKK)nX-NH2 (m = 0, 3; n = 2, 3; X = I, L, and V) as the model molecules and studied the conformation regulation through N-terminus lipidation and their formulation with surfactants. The structural and morphological transition of peptide self-assemblies have also been investigated via transmission electron microscopy, atomic force microscopy, circular dichroism spectroscopy, and small-angle neutron scattering. With the terminal alkylation, the molecular conformation changed from random coil to ß-sheet or α-helix. The antimicrobial activities of alkylated peptide were different. C16-G3(IIKK)3I-NH2 showed antimicrobial activity against Streptococcus mutans, while C16-(IIKK)2I-NH2 and C16-G3(IIKK)2I-NH2 did not kill the bacteria. The surfactant sodium dodecyl sulfonate could rapidly induce the self-assemblies of alkylated peptides (C16-(IIKK)2I-NH2, C16-G3(IIKK)2I-NH2, C16-G3(VVKK)2V-NH2) from nanofibers to micelles, along with the conformation changing from ß-sheet to α-helix. The cationic surfactant hexadecyl trimethyl ammonium bromide made the lipopeptide nanofibers thinner, and nonionic surfactant polyoxyethylene (23) lauryl ether (C12EO23) induced the nanofibers much more intensively. Both the activity and the conformation of the α-helical peptide could be modulated by lipidation. Then, the self-assembled morphologies of alkylated peptides could also be further regulated with surfactants through hydrophobic, electrostatic, and hydrogen-bonding interactions. These results provided useful strategies to regulate the molecular conformations in peptide-based material functionalization.

Metabolomics analysis of Pulsatilla decoction on treatment of wetness-heat-induced diarrhea in rats based on UPLC-Q/TOF-MS/MS.

Pulsatilla decoction (PD) is a classical prescription in traditional Chinese medicine that has therapeutic effects on wetness-heat-induced diarrhea (WHD). To investigate the therapeutic effects of PD in the treatment of WHD and elucidate the potential mechanism, we used a metabolomics strategy on the base of ultraperformance liquid chromatography coupled with quadrupole time-of-flight/mass spectrometry (UPLC-Q/TOF-MS/MS) and analyzed the serum samples of 32 rats to identify differential metabolites and pathways associated with the PD treatment of WHD. With variable importance for projection >1.0 in the Orthogonal partial least-squares discriminant analysis (OPLS-DA ) models and FC ≥1.2 or ≤0.8, 67 differential metabolites in the model and control groups and 33 differential metabolites in the model and PD groups were screened. A total of 23 differential metabolites were selected based on Venny analysis. Functional analysis showed that the differential metabolites identified were primarily involved in pentose and glucuronate interconversions, glycerophospholipid metabolism, tryptophan metabolism, starch and sucrose metabolism, and glycerolipid metabolism. This study suggested that PD exerts inhibitory effects on WHD. In particular, the significant roles of PD for treating WHD lie in regulating perturbed energy metabolism, glycerophospholipid metabolism and glycerolipid metabolism, and promoting lysoPC production restoring the function of intestinal tract.

IO4- -stimulated crosslinking of catechol-conjugated hydroxyethyl chitosan as a tissue adhesive.

Catechol-functionalized polymers are of particular interest because of their strong water-resistant adhesive properties. Hydroxymethyl chitosan (HECTS) has been used as an implantable biomaterial having good water solubility, biodegradability and biocompatibility. Here, hydrocaffeic acid (HCA) grafted HECTS (HCA-g-HECTS) was prepared through carbodiimide coupling and the tethered catechol underwent periodate ( IO4- )-stimulated mono and double cross-linking with genipin. The gelation time of these cross-linked HCA-g-HECTS hydrogels decreased with increasing molar ratio of cross-linker to grafted catechol group, increasing temperature, or the addition of genipin. Under the same molar ratio of cross-linker to catechol, IO4- -induced cross-linked HCA-g-HECTS hydrogels exhibited much stronger storage modulus and temperature stability than hydrogels made by Fe3+ -triggered cross-linking. The IO4- -stimulated HCA-g-HECTS hydrogels were biocompatible on a cellular level when the molar ratio of IO4- to catechol group was less than 0.5:1. The hydrogels prepared with a 0.125:1 molar ratio of IO4- to catechol group exhibited high adhesion strength of 73.56 kPa against wet rat skin, and a higher adhesion strength than sutures in a rat wound closure model. This biocompatible IO4- -stimulated HCA-g-HECTS hydrogel may represent a promising new tissue adhesive. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 2018. © 2018 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 107B: 582-593, 2019.

Evaluation of a photocrosslinkable hydroxyethyl chitosan hydrogel as a potential drug release system for glaucoma surgery.

Hydroxyethyl chitosan (HECTS) is a critical derivative of chitosan that has been widely used as biomedical materials due to great water-solubility and excellent biocompatibility. Here, photosensitive hydroxyethyl chitosan was synthesized by introducing azide group on NH2 of HECTS (HECTS-AZ), afterwards FTIR and 1H NMR spectra were detected to confirm the formation of HECTS-AZ. The solution of HECTS-AZ can achieve a sol-gel transition through UV irradiation for 30 s. The evaluation of biocompability and biodegradability in vivo was conducted in rats, visual and pathological examinations exhibited the HECTS-AZ has excellent biocompability and degradation time of the hydrogel is more than 14 weeks. Furthermore, HECTS-AZ hydrogel as an ocular drug delivery system loading heparin was prepared to implant under sclera of rabbit after glaucoma filtration surgery (GFS). The experimental results demonstrated the heparin loaded hydrogel can effectively maintain filtration bleb and lowing intraocular pressure (IOP) after GFS for prolonged time. Besides, obvious inflammatory reactions and side effects have not been observed in ocular during the experimental period. In conclusion, the HECTS-AZ hydrogel is a potential drug delivery device for the treatment of glaucoma and other ocular diseases.