Protective effects of Jing-Si-herbal-tea in inflammatory cytokines-induced cell injury on normal human lung fibroblast via multiomic platform analysis.

Objectives: The protective effects and related mechanisms of Jing-Si herbal tea (JSHT) were investigated in cellular damage mediated by pro-inflammatory cytokines, including interleukin (IL)-1ß, IL-6, and tumor necrosis factor-α, on normal human lung fibroblast by multiomic platform analysis. Materials and Methods: The in silico high-throughput target was analyzed using pharmacophore models by BIOVIA Discovery Studio 2022 with ingenuity pathway analysis software. To assess cell viability, the study utilized the MTT assay technique. In addition, the IncuCyte S3 ZOOM System was implemented for the continuous monitoring of cell confluence of JSHT-treated cytokine-injured HEL 299 cells. Cytokine concentrations were determined using a Quantibody Human Inflammation Array. Gene expression and signaling pathways were determined using next-generation sequencing. Results: In silico high-throughput target analysis of JSHT revealed ingenuity in canonical pathways and their networks. Glucocorticoid receptor signaling is a potential signaling of JSHT. The results revealed protective effects against the inflammatory cytokines on JSHT-treated HEL 299 cells. Transcriptome and network analyses revealed that induction of helper T lymphocytes, TNFSF12, NFKB1-mediated relaxin signaling, and G-protein coupled receptor signaling play important roles in immune regulatory on JSHT-treated cytokine-injured HEL 299 cells. Conclusion: The findings from our research indicate that JSHT holds promise as a therapeutic agent, potentially offering advantageous outcomes in treating virus infections through various mechanisms. Furthermore, the primary bioactive components in JSHT justify extended research in antiviral drug development, especially in the context of addressing coronavirus.

Exercise quantification from single camera view markerless 3D pose estimation.

Sports physiotherapists and coaches are tasked with evaluating the movement quality of athletes across the spectrum of ability and experience. However, the accuracy of visual observation is low and existing technology outside of expensive lab-based solutions has limited adoption, leading to an unmet need for an efficient and accurate means to measure static and dynamic joint angles during movement, converted to movement metrics useable by practitioners. This paper proposes a set of pose landmarks for computing frequently used joint angles as metrics of interest to sports physiotherapists and coaches in assessing common strength-building human exercise movements. It then proposes a set of rules for computing these metrics for a range of common exercises (single and double drop jumps and counter-movement jumps, deadlifts and various squats) from anatomical key-points detected using video, and evaluates the accuracy of these using a published 3D human pose model trained with ground truth data derived from VICON motion capture of common rehabilitation exercises. Results show a set of mathematically defined metrics which are derived from the chosen pose landmarks, and which are sufficient to compute the metrics for each of the exercises under consideration. Comparison to ground truth data showed that root mean square angle errors were within 10° for all exercises for the following metrics: shin angle, knee varus/valgus and left/right flexion, hip flexion and pelvic tilt, trunk angle, spinal flexion lower/upper/mid and rib flare. Larger errors (though still all within 15°) were observed for shoulder flexion and ASIS asymmetry in some exercises, notably front squats and drop-jumps. In conclusion, the contribution of this paper is that a set of sufficient key-points and associated metrics for exercise assessment from 3D human pose have been uniquely defined. Further, we found generally very good accuracy of the Strided Transformer 3D pose model in predicting these metrics for the chosen set of exercises from a single mobile device camera, when trained on a suitable set of functional exercises recorded using a VICON motion capture system. Future assessment of generalization is needed.

Mental Illness Diagnoses May Not Cause All Mental Symptoms: A Simulation Study for Major Depressive Episodes, Dysthymic Disorder, and Manic Episodes.

Objectives This study aims to understand the statistical significance of the associations between diagnoses and symptoms based on simulations that have been used to understand the interpretability of mental illness diagnoses. Methods The symptoms for the diagnosis of major depressive episodes, dysthymic disorder, and manic episodes were extracted from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR, American Psychiatric Association, Philadelphia, Pennsylvania). Without real-world symptom data, we simulated populations using various combinations of symptom prevalence and correlations. Assuming symptoms occurred with similar prevalence and correlations, for each combination of symptom prevalence (0.05, 0.1, 0.3, 0.5, and 0.7) and correlation (0, 0.1, 0.4, 0.7, and 0.9), 100 cohorts with 10,000 individuals were randomly created. Diagnoses were made according to the DSM-IV-TR criteria. The associations between the diagnoses and their input symptoms were quantified with odds ratios and correlation coefficients. P-values from 100 cohorts for each combination of symptom prevalence and correlation were summarized. Results Three mental illness diagnoses were not significantly correlated with their own symptoms in all simulations, particularly when symptoms were not correlated, except for the symptom in the major criteria of major depressive episodes or dysthymic disorder. The symptoms for the diagnosis of major depressive episodes and dysthymic disorder were significantly correlated with these two diagnoses in some simulations, assuming 0.1, 0.4, 0.7, or 0.9 symptom correlations, except for one symptom. The overlap in the input symptoms for the diagnosis of major depressive episodes and dysthymic disorder also leads to significant correlations between these two diagnoses, assuming 0.1, 0.4, 0.7, and 0.9 correlations between input symptoms. Manic episodes are not significantly associated with the input symptoms of major depressive episodes and dysthymic disorder. Conclusion There are challenges to establish the causation between psychiatric symptoms and mental illness diagnoses. There is insufficient prevalence and incidence data to show all psychiatric symptoms exist or can be observed in patients. The diagnostic accuracy of symptoms to detect a disease cause is far from perfect. Assuming the symptoms of three mood disorders may present in patients, three diagnoses are not significantly associated with all psychiatric symptoms used to diagnose them. The diagnostic criteria of the three diagnoses have not been designed to guarantee significant associations between symptoms and diagnoses. Because statistical associations are important for making causal inferences, there may be a lack of causation between diagnoses and symptoms. Previous research has identified factors that lead to insignificant associations between diagnoses and symptoms, including biases due to data processing and a lack of epidemiological evidence to support the design of mental illness diagnostic criteria.

Characterization of chicken-derived antibody against Alpha-Enolase of Streptococcus pneumoniae.

Streptococcus pneumoniae is a clinically relevant pathogen notorious for causing pneumonia, meningitis, and otitis media in immunocompromised patients. Currently, antibiotic therapy is the most efficient treatment for fighting pneumococcal infections. However, an arise in antimicrobial resistance in S. pneumoniae has become a serious health issue globally. To resolve the problem, alternative and cost-effective strategies, such as monoclonal antibody-based targeted therapy, are needed for combating bacterial infection. S. pneumoniae alpha-enolase (spEno1), which is thought to be a great target, is a surface protein that binds and converts human plasminogen to plasmin, leading to accelerated bacterial infections. We first purified recombinant spEno1 protein for chicken immunization to generate specific IgY antibodies. We next constructed two single-chain variable fragments (scFv) antibody libraries by phage display technology, containing 7.2 × 107 and 4.8 × 107 transformants. After bio-panning, ten scFv antibodies were obtained, and their binding activities to spEno1 were evaluated on ELISA, Western blot and IFA. The epitopes of spEno1 were identified by these scFv antibodies, which binding affinities were determined by competitive ELISA. Moreover, inhibition assay displayed that the scFv antibodies effectively inhibit the binding between spEno1 and human plasminogen. Overall, the results suggested that these scFv antibodies have the potential to serve as an immunotherapeutic drug against S. pneumoniae infections.

Coupling capillary electrophoresis with mass spectrometry for the analysis of oxidized phospholipids in human high-density lipoproteins.

The oxidized 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphocholine (ox-PAPC) products in human high-density lipoproteins (HDLs) were investigated by low-flow capillary electrophoresis-mass spectrometry (low-flow CE-MS). To accelerate the optimization, native PAPC (n-PAPC) standard was first analyzed by a commercial CE instrument with a photodiode array detector. The optimal separation buffer contained 60% (v/v) acetonitrile, 40% (v/v) methanol, 20 mM ammonium acetate, 0.5% (v/v) formic acid, and 0.1% (v/v) water. The selected separation voltage and capillary temperature were 20 kV and 23°C. The optimal CE separation buffer was then used for the low-flow CE-MS analysis. The selected MS conditions contained heated capillary temperature (250°C), capillary voltage (10 V), and injection time (1 s). No sheath gas was used for MS. The linear range for n-PAPC was 2.5-100.0 µg/mL. The coefficient of determination (R2 ) was 0.9918. The concentration limit of detection was 1.52 µg/mL, and the concentration limit of quantitation was 4.60 µg/mL. The optimal low-flow CE-MS method showed good repeatability and sensitivity. The ox-PAPC products in human HDLs were determined based on the in vitro ox-PAPC products of n-PAPC standard. Twenty-one ox-PAPC products have been analyzed in human HDLs. Uremic patients showed significantly higher levels of 15 ox-PAPC products than healthy subjects.

The Predictors and Outcomes of Functional Mitral Stenosis following Surgical Mitral Valve Repair: A Retrospective Analysis.

To optimize mitral valve repair outcomes, it is crucial to comprehend the predictors of functional mitral valve stenosis (FMS), to enhance preoperative assessments, and to adapt intraoperative treatment strategies. This study aimed to identify FMS risk factors, contributing valuable insights for refining surgical techniques. Among 228 selected patients, 215 underwent postoperative echocardiography follow-ups, and 36 met the FMS criteria based on a mean trans-mitral pressure gradient of >5 mmHg. Patients with FMS exhibited higher pulmonary systolic arterial pressure and increased late mortality during the follow-up. Univariable logistic regression analysis identified several risk factors for FMS, including end-stage renal disease, anterior leaflet lesion, concomitant aortic valve replacement, smaller ring size, ring type, and neochordae implantation. Conversely, resection alone and resection combined with neochordae implantation had protective effects against FMS. Multivariable logistic regression analysis revealed that smaller ring sizes and patch repair independently predicted FMS. When focusing on degenerative mitral regurgitation, the neochordae implantation without resection in leaflet repair, emerged as an independent predictor of FMS. Surgeons should weigh the substantial impact of surgical procedures on postoperative trans-mitral pressure gradients, emphasizing preoperative evaluation and techniques such as precise ring size assessment and effective leaflet management.

Elucidating the Mechanisms of Sodium Benzoate in Alzheimer Disease: Insights from Quantitative Proteomics Analysis of Serum Samples.

BACKGROUND: N-methyl-D-aspartate receptors (NMDARs) are crucial components of brain function involved in memory and neurotransmission. Sodium benzoate is a promising NMDAR enhancer and has been proven to be a novel, safe, and efficient therapy for patients with Alzheimer disease (AD). However, in addition to the role of sodium benzoate as an NMDA enhancer, other mechanisms of sodium benzoate in treating AD are still unclear. To elucidate the potential mechanisms of sodium benzoate in Alzheimer disease, this study employed label-free quantitative proteomics to analyze serum samples from AD cohorts with and without sodium benzoate treatment. METHODS: The serum proteins from each patient were separated into 24 fractions using an immobilized pH gradient, digested with trypsin, and then subjected to nanoLC‒MS/MS to analyze the proteome of all patients. The nanoLC‒MS/MS data were obtained with a label-free quantitative proteomic approach. Proteins with fold changes were analyzed with STRING and Cytoscape to find key protein networks/processes and hub proteins. RESULTS: Our analysis identified 861 and 927 protein groups in the benzoate treatment cohort and the placebo cohort, respectively. The results demonstrated that sodium benzoate had the most significant effect on the complement and coagulation cascade pathways, amyloidosis disease, immune responses, and lipid metabolic processes. Moreover, Transthyretin, Fibrinogen alpha chain, Haptoglobin, Apolipoprotein B-100, Fibrinogen beta chain, Apolipoprotein E, and Alpha-1-acid glycoprotein 1 were identified as hub proteins in the protein‒protein interaction networks. CONCLUSIONS: These findings suggest that sodium benzoate may exert its influence on important pathways associated with AD, thus contributing to the improvement in the pathogenesis of the disease.

Bioactive phytochemicals from the tubers of Bletilla striata Rchb.f.

Thirty-four phytochemicals were isolated from dry tubers of Bletilla striata Rchb.f. The compounds were classified as bibenzyls 1-14, dihydrophenanthrenes 15, 17, 20, 21, phenanthrenes 16, 18, 19, simple benzoids 22-24, a fatty acid 25, glucosyloxybenzyl 2-isobutylmalates 26-32, and glucosyloxybenzyl cinnamates 33, 34. Compounds 1-4, 7, 8, 11, 12, and 16 inhibited melanogenesis (17.96-55.27%) induced by α-MSH in B16F10 cells at 10-40 µM. However, compounds 9, 10, 17, 18, and 21 exhibited significant cytotoxicity against melanomas, with IC50 values of 12-34 µM. Additionally, compounds 15, 17, 19, 20, 23, 31, and 33 reduced the ROS generation induced by H2O2 in HaCaT cells at 6.25-100 µM. In particular, compounds 15, 19, and 20 strongly inhibited ROS generation, with IC50 values of 2.15-9.48 µM. Consequently, compounds 1-4, 7-12, and 15-21 may be the strongest leads to follow in B. striata extract for further research on the skin disorders, hyperpigmentation, melanoma, and ageing.

Crystal structure and functional implications of cyclic di-pyrimidine-synthesizing cGAS/DncV-like nucleotidyltransferases.

Purine-containing nucleotide second messengers regulate diverse cellular activities. Cyclic di-pyrimidines mediate anti-phage functions in bacteria; however, the synthesis mechanism remains elusive. Here, we determine the high-resolution structures of cyclic di-pyrimidine-synthesizing cGAS/DncV-like nucleotidyltransferases (CD-NTases) in clade E (CdnE) in its apo, substrate-, and intermediate-bound states. A conserved (R/Q)xW motif controlling the pyrimidine specificity of donor nucleotide is identified. Mutation of Trp or Arg from the (R/Q)xW motif to Ala rewires its specificity to purine nucleotides, producing mixed purine-pyrimidine cyclic dinucleotides (CDNs). Preferential binding of uracil over cytosine bases explains the product specificity of cyclic di-pyrimidine-synthesizing CdnE to cyclic di-UMP (cUU). Based on the intermediate-bound structures, a synthetic pathway for cUU containing a unique 2'3'-phosphodiester linkage through intermediate pppU[3'-5']pU is deduced. Our results provide a framework for pyrimidine selection and establish the importance of conserved residues at the C-terminal loop for the specificity determination of CD-NTases.

Identification of a potential prognostic plasma biomarker of acute ischemic stroke via untargeted LC-MS metabolomics.

PURPOSE: Stroke is the sudden death of brain cells in a localized area due to an inadequate blood flow or blood vessel rupture, and it seriously affects the quality of life. The metabolite biomarkers are needed for predicting the functional outcome of acute ischemic stroke (AIS). EXPERIMENTAL DESIGN: To identify biomarkers for AIS, untargeted LC/MS metabolomics was performed on plasma samples from subjects with favorable prognosis (mRS ≤ 2) and unfavorable prognosis (mRS > 2). The identified markers were further absolutely quantified by a targeted MRM approach. RESULTS: There were 10 upregulated and 26 downregulated markers. Among these candidates, one was successfully identified as glycocholic acid and then absolutely quantified in plasma samples. Glycocholic acid could discriminate between subjects with favorable and unfavorable prognosis with an area under the curve (AUC) of 0.68 and odds ratio of 5.88. CONCLUSIONS AND CLINICAL RELEVANCE: Glycocholic acid was identified as a potential plasma metabolite marker of non-progressive outcomes after ischemic stroke and could serve as predictive prognostic markers for clinical acute stroke outcomes.

Herbs for lochia discharge used among postpartum women in Taiwan.

ETHNOPHARMACOLOGICAL RELEVANCE: In the traditional Taiwanese culture of "postpartum confinement", the term "lochia discharge" is a synonym for assisting postpartum uterine involution. Postpartum women in Taiwan consult traditional Chinese medicine (TCM) pharmacies to obtain various TCM formulations that facilitate lochia discharge. AIM OF THE STUDY: As an ethnopharmacy study, we aimed to conduct field investigations to explore the herbal composition of TCM formulations for lochia discharge provided by TCM pharmacies in Taiwan and to identify the pharmaceutical implications of these TCM formulations. MATERIALS AND METHODS: Through stratified sampling, we collected 98 formulations for postpartum lochia discharge from TCM pharmacies, which used a total of 60 medicinal materials. RESULTS: The most common plant families of the medicinal materials found in Taiwanese lochia discharge formulations were Fabaceae and Lauraceae. Abiding by the TCM theory of nature and flavor, most drugs were warm in nature and sweet in flavor, and predominantly focused on the traditional functions of qi tonifying and blood activating. Correlation and network analyses of the medicinal components of lochia discharge formulations identified 11 core herbs, which, in the order of most to least frequently used, include Angelica sinensis, Ligusticum striatum, Glycyrrhiza uralensis, Zingiber officinale, Prunus persica, Eucommia ulmoides, Leonurus japonicus, Lycium chinense, Hedysarum polybotrys, Rehmannia glutinosa, and Paeonia lactiflora. These 11 herbs formed a total of 136 drug combinations in the 98 formulations, with 2-7 herbs in each combination. In addition, in the center of the network were A. sinensis and L. striatum, which jointly appeared in 92.8% of the formulations analyzed. CONCLUSIONS: To our knowledge, this is the first study to systematically review lochia discharge formulations in Taiwan. The results of this study could provide an important basis for subsequent research in the clinical efficacy of Taiwanese lochia discharge formulations and the pharmacological mechanisms of their herbal components.

The Upper Limits of Risk Ratios and Recommendations for Reporting Risk Ratios, Odds Ratios, and Rate Ratios.

Background Relative measures, including risk ratios (RRs) and odds ratios (ORs), are reported in many epidemiological studies. RRs represent how many times a condition is likely to develop when exposed to a risk factor. The upper limit of RRs is the multiplicative inverse of the baseline incidence. Ignoring the upper limits of RRs can lead to reporting exaggerated relative effect sizes. Objectives This study aims to demonstrate the importance of such upper limits for effect size reporting via equations, examples, and simulations and provide recommendations for the reporting of relative measures. Methods Equations to calculate RRs and their 95% confidence intervals (CIs) were listed. We performed simulations with 10,000 simulated subjects and three population variables: proportions at risk (0.05, 0.1, 0.3, 0.5, and 0.8), baseline incidence (0.05, 0.1, 0.3, 0.5, and 0.8), and RRs (0.5, 1.0, 5.0, 10.0, and 25.0). Subjects were randomly assigned with a risk based on the set of proportions-at-risk values. A disease occurred based on the baseline incidence among those not at risk. The incidence of those at risk was the product of the baseline incidence and the RRs. The 95% CIs of RRs were calculated according to Altman. Results The calculation of RR 95% CIs is not connected to the RR upper limits in equations. The RRs in the simulated populations at risk could reach the upper limits of RRs: multiplicative inverse of the baseline incidence. The upper limits to the derived RRs were around 1.25, 2, 3.3, 10, and 20, when the assumed baseline incidence rates were 0.8, 0.5, 0.3, 0.2, and 0.05, respectively. We demonstrated five scenarios in which the RR 95% CIs might exceed the upper limits. Conclusions Statistical significance does not imply the RR 95% CIs not exceeding the upper limits of RRs. When reporting RRs or ORs, the RR upper limits should be assessed. The rate ratio is also subject to a similar upper limit. In the literature, ORs tend to overestimate effect sizes. It is recommended to correct ORs that aim to approximate RRs assuming outcomes are rare. A reporting guide for relative measures, RRs, ORs, and rate ratios, is provided. Researchers are recommended to report whether the 95% CIs of relative measures, RRs, ORs, and rate ratios, overlap with the range of upper limits and discuss whether the relative measure estimates may exceed the upper limits.

Critical Hierarchical Appraisal and Reporting Tool for Composite Measures (CHAOS).

Background Composite measures are often used to represent certain concepts that cannot be measured with single variables and can be used as diagnoses, prognostic factors, or outcomes in clinical or health research. For example, frailty is a diagnosis confirmed based on the number of age-related symptoms and has been used to predict major health outcomes. However, undeclared assumptions and problems are prevalent among composite measures. Thus, we aim to propose a reporting guide and an appraisal tool for identifying these assumptions and problems. Methods We developed this reporting and assessment tool based on evidence and the consensus of experts pioneering research on index mining and syndrome mining. We designed a development framework for composite measures and then tested and revised it based on several composite measures commonly used in medical research, such as frailty, body mass index (BMI), mental illness diagnoses, and innovative indices mined for mortality prediction. We extracted review questions and reporting items from various issues identified by the development framework. This panel reviewed the identified issues, considered other aspects that might have been neglected in previous studies, and reached a consensus on the questions to be used by the reporting and assessment tool. Results We selected 19 questions in seven domains for reporting or critical assessment. Each domain contains review questions for authors and readers to critically evaluate the interpretability and validity of composite measures, which include candidate variable selection, variable inclusion and assumption declaration, data processing, weighting scheme, methods to aggregate information, composite measure interpretation and justification, and recommendations on the use. Conclusions For all seven domains, interpretability is central with respect to composite measures. Variable inclusion and assumptions are important clues to show the connection between composite measures and their theories. This tool can help researchers and readers understand the appropriateness of composite measures by exploring various issues. We recommend using this Critical Hierarchical Appraisal and repOrting tool for composite measureS (CHAOS) along with other critical appraisal tools to evaluate study design or risk of bias.

The identification of a potential plasma metabolite marker for Alzheimer's disease by LC-MS untargeted metabolomics.

BACKGROUND AND AIMS: Alzheimer's disease (AD), the most common type of dementia, is hard to recognize early, resulting in delayed treatment and poor outcome. At present, there is neither reliable, non-invasive methods to diagnose it accurately and nor effective drugs to recover it. Discovery and quantification of novel metabolite markers in plasma of AD patients and investigation of the correlation between the markers and AD assessment scores. MATERIALS AND METHODS: Untargeted liquid chromatography-mass spectrometry (LC-MS)-based metabolomics with LC-quadrupole- time-of-flight (Q-TOF) was performed in plasma samples of age-matched AD patients and healthy controls. The potential markers were further quantified with targeted multiple reaction monitoring (MRM) approach. RESULTS: Among the candidates, progesterone, and 3-indoleacetic acid (3-IAA) were successfully identified and then validated in 50 plasma samples from 25 AD patients and 25 matched normal controls with MRM approach. As a result, 3-IAA was significantly altered in AD patients and correlated with some AD assessment scores. CONCLUSION: By using untargeted LC-MS metabolomic and LC-MRM approaches to analyze plasma metabolites of AD patients and normal subjects, 3-IAA was discovered and quantified to be significantly altered in AD patients and correlated with several AD assessment scores.

Online 2D High-pH and Low-pH Reversed-Phase Nano-LC-MS/MS System for Deep Proteome Analysis.

In bottom-up proteomic profiling, the complexity of proteome composition and wide dynamic range has created challenges on the limited number of protein identification and proteome coverage, especially in sample input-limited nanoflow (nano) LC-MS/MS analysis. Herein, we developed a fully automatic online 2D nano-LC-MS/MS system using both high-pH and low-pH reverse phase (RP) LCs on a single LC instrument toward comprehensive proteomics analysis. Compared to conventional microflow 2D-LC, the high-pH RP trapping column demonstrated a low sample requirement of cellular protein digest at the µg level with good fractionation resolution of >90% peptides in a single fraction. Compared to the offline 2D RP-RP nano-LC-QTOF using C18-HPLC column and C18-Stage Tip, and 1D nano-LC-QTOF system, superior coverage was observed on the higher number of identified protein groups/unique peptides by 1.35-/1.68-, 1.46-/1.75-, and 3.21-/4.35-fold, respectively, using an online 2D RP-RP nano-LC-QTOF mass spectrometer. On the evolution of quantitation performance, the online 2D high-/low-pH RP data-independent acquisition (DIA) showed a higher reproducibility in protein groups intensity (R2 > 0.977) and more quantified proteins than that obtained using the offline 2D high-/low-pH RP DIA approach. Using an advanced Orbitrap Exploris 480 mass spectrometer, ∼1.9-fold higher proteome coverage was also observed in our 2D online RP-RP system (6039 protein groups) compared to the 1D nano-LC system (3133 protein groups). In summary, the online 2D nano-LC-MS/MS platform can be a sensitive and robust approach compatible with conventional nano-LC instruments for deep proteome coverage of trace amounts of samples.

Bevacizumab and Atezolizumab for Unresectable Hepatocellular Carcinoma: Real-world Data in Taiwan-Tainan Medical Oncology Group H01 Trial.

BACKGROUND/AIM: The combination of bevacizumab and atezolizumab (Bev-Ate) has been established as a standard first-line systemic treatment option for unresectable hepatocellular carcinoma (HCC) since 2020. This study examined the outcomes of HCC patients who received the combination in southern Taiwan. PATIENTS AND METHODS: All patients were enrolled from four hospitals in Taiwan. They received Bev-Ate therapy for unresectable HCC. RESULTS: Thirty-five patients were included; 28 (80%) had Barcelona Clinic Liver Cancer stage C disease. Hepatitis etiology was chronic hepatitis B and C in 63% and 17% of patients, respectively. Eleven (31%) patients had received prior systemic treatment for unresectable HCC. The response rate was 51%, and the disease control rate was 72% for all patients. The median progression-free survival (PFS) and overall survival (OS) was 5.2 and 22.2 months, respectively. For patients who received prior systemic treatment, the efficacy of Bev-Ate in terms of response rates was similar compared with those without prior systemic treatment. Patients who received lower doses of bevacizumab (<15 mg/kg per dose) had non-inferior PFS and OS compared with those receiving a standard dose of bevacizumab. The incidence of proteinuria of all grades (15.8%) was less common when lower doses of bevacizumab were used. CONCLUSION: Real world data from HCC patients in southern Taiwan disclosed that the efficacy outcomes of Bev-Ate treatment were generally consistent with those of clinical trials in other countries. In patients who were exposed to prior systemic treatment or who received lower doses of bevacizumab, the Bev-Ate regimen retained its clinical efficacy.

Determination of oxidized 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphocholine products in human very low-density lipoproteins by nonaqueous low-flow capillary electrophoresis-mass spectrometry.

A simple and fast low-flow capillary electrophoresis-mass spectrometry (low-flow CE-MS) method has been developed to analyze oxidized 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphocholine (ox-PAPC) products in human very low-density lipoproteins (VLDLs). Native PAPC standard was analyzed to optimize the low-flow CE-MS method. The optimal CE conditions included separation buffer (60% (v/v) acetonitrile, 40% (v/v) methanol, 0.1% (v/v) water, 0.5% (v/v) formic acid, 20 mM ammonium acetate), sheath liquid (60% (v/v) acetonitrile, 40% (v/v) methanol, 0.1% (v/v) water, 20 mM ammonium acetate), separation voltage (20 kV), separation capillary internal diameter (i.d.) (75 µm), separation capillary temperature (23˚C) and sample injection time (6 s). The selected MS conditions included heated capillary temperature (250°C), capillary voltage (10 V), and injection time (1 s). Sheath gas was not used in this study. The total ion chromatograms (TICs), extracted ion chromatograms (EICs) and MS spectra of native PAPC standard and its in vitro oxidation products showed good repeatability and sensitivity. To determine the ox-PAPC products in human VLDLs, the EICs and MS spectra of VLDLs were compared with the in vitro oxidation products of native PAPC standard. For native PAPC standard, the measured linear range was 2.5 - 100.0 µg/mL, and the coefficients of determination (R2) was 0.9994. The concentration limit of detection (LOD) was 0.44 µg/mL, and the concentration limit of quantitation (LOQ) was 1.34 µg/mL. A total of 21 ox-PAPC products were analyzed for the VLDLs of healthy and uremic subjects. The levels of 7 short-chain and 5 long-chain ox-PAPC products on uremic VLDLs were significantly higher than healthy VLDLs. This simple low-flow CE-MS method might be a good alternative for LC-MS for the analysis of ox-PAPC products. Furthermore, it might also help scientists to expedite the search for uremic biomarkers.

Improvement of enzymatic cross-linking of ovalbumin and ovotransferrin induced by transglutaminase with heat and reducing agent pretreatment.

The effects of transglutaminase (TGase, 1.0 unit/mL) with heat (95 °C, 5 min), 2-mercaptoethanol (2-ME, 0.83 %), and l-cysteine (l-Cys, 50 mM) pretreatment on the cross-linking of ovalbumin (OVA) and ovotransferrin (OVT) were investigated. SDS-PAGE revealed that although the polymerization of OVA and OVT did not occur after 3 h of incubation at 40 °C with TGase, OVA polymerized into high molecular weight polymers following TGase with 2-ME and heat pretreatment after 3 h of incubation. The surface hydrophobicity and reactive sulfhydryl (SH) groups of OVA samples significantly increased from 4065.7 ± 136.7 and 89.3 ± 1.2 SH groups (µmol/g) to 31483.6 ± 342.7 and 119.5 ± 3.7 SH groups (µmol/g), respectively. Similar results were obtained for OVT with TGase and l-Cys pretreatment and a 3-h incubation at 40 °C. The use of TGase, a reducing agent, and/or heat pretreatment can be used for the polymerization of OVA and OVT.

Influence of confirmed viral infection on adult acute fulminant myocarditis supported with extracorporeal membrane oxygenation.

BACKGROUND: The impact of etiologies of acute fulminant myocarditis (AFM), which requires extracorporeal membrane oxygenation (ECMO), on clinical outcomes remains unknown. This study aimed to investigate the risk factors for ECMO weaning and mortality among patients with AFM due to viral etiologies in a tertiary referral medical center. METHODS: We included 33 adults with AFM who received ECMO and were admitted between January 2002 and January 2021. General demographics, laboratory data, echocardiography findings, and long-term outcomes were analyzed for confirmed viral etiology and unconfirmed etiology groups. RESULTS: The overall hospital survival rate was 54.5%. The age, sex, severity of the hemodynamic condition, and cardiac rhythm were similar between the two groups. Multivariate Cox regression analysis revealed that a confirmed viral etiology (HR 4.201, 95% CI 1.061-16.666), peri-ECMO renal replacement therapy (RRT) (HR 9.804, 1.140-83.333) and a high positive end-expiratory pressure (PEEP) in the ventilator settings at 24 h after ECMO (HR 1.479, 1.020-2.143) were significant prognostic factors for in-hospital mortality. Peri-ECMO RRT was also a significant negative prognostic factor for successful ECMO weaning (OR 0.061, 0.006-0.600) in the multivariate logistic model. CONCLUSIONS: Among AFM patients receiving ECMO support, RRT use was associated with a decreased chance of survival to ECMO weaning. Multiple organ dysfunction and a high PEEP were also predictive of a lower chance of hospital survival. Those with a confirmed diagnosis of viral myocarditis may require more medical attention due to the higher risk of hospital mortality than those without a definite diagnosis.

Recent advances in LC-MS-based metabolomics for clinical biomarker discovery.

The employment of liquid chromatography-mass spectrometry (LC-MS) untargeted and targeted metabolomics has led to the discovery of novel biomarkers and improved the understanding of various disease mechanisms. Numerous strategies have been reported to expand the metabolite coverage in LC-MS-untargeted and targeted metabolomics. To improve the sensitivity of low-abundance or poor-ionized metabolites for reducing the amount of clinical sample, chemical derivatization methods are used to target different functional groups. Proper sample preparation is beneficial for reducing the matrix effect, maintaining the stability of the LC-MS system, and increasing the metabolite coverage. Machine learning has recently been integrated into the workflow of LC-MS metabolomics to accelerate metabolite identification and data-processing automation, and increase the accuracy of disease classification and clinical outcome prediction. Due to the rapidly growing utility of LC-MS metabolomics in discovering disease markers, this review will address the recent advances in the field and offer perspectives on various strategies for expanding metabolite coverage, chemical derivatization, sample preparation, clinical disease markers, and machining learning for disease modeling.