Functional assessment of a novel biallelic MYH3 variation causing CPSKF1B (contractures, pterygia, and spondylocarpotarsal fusion syndrome1B).

BACKGROUND: The MYH3-associated myosinopathies comprise a spectrum of rare neuromuscular disorders mainly characterized by distal arthrogryposis with or without other features like pterygia and vertebrae fusion. CPSKF1B (contractures, pterygia, and spondylocarpotarsal fusion syndrome1B) is the only known autosomal recessiveMYH3-associated myosinopathy so far, with no more than two dozen cases being reported. MATERIALS AND METHODS: A boy with CPSKF1B was recruited and subjected to a comprehensive clinical and imaging evaluation. Genetic detection with whole-exome sequencing (WES) was performed on the patient and extended family members to identify the causative variation. A series of in silico and in vitro investigations were carried out to verify the pathogenicity of the two variants of the identified compound heterozygous variation. RESULTS: The patient exhibited moderate CPSKF1B symptoms including multiarticular contractures, webbed neck, and spondylocarpotarsal fusion. WES detected a compound heterozygous MYH3 variation consisting of two variants, namely NM_002470.4: c.3377A>G; p. (E1126G) and NM_002470.4: c.5161-2A>C. It was indicated that the NM_002470.4: c.3377A>G; p. (E1126G) variant mainly impaired the local hydrogen bond formation and impacted the TGF-B pathway, while the NM_002470.4: c.5161-2A>C variant could affect the normal splicing of pre-mRNA, resulting in the appearance of multiple abnormal transcripts. CONCLUSIONS: The findings of this study expanded the mutation spectrum of CPSKF1B, provided an important basis for the counseling of the affected family, and also laid a foundation for the functional study of MYH3 mutations.

Development and validation of an interpretable Markov-embedded multilabel model for predicting risks of multiple postoperative complications among surgical inpatients: a multicenter prospective cohort study.

BACKGROUND: When they encounter various highly related postoperative complications, existing risk evaluation tools that focus on single or any complications are inadequate in clinical practice. This seriously hinders complication management because of the lack of a quantitative basis. An interpretable multilabel model framework that predicts multiple complications simultaneously is urgently needed. MATERIALS AND METHODS: The authors included 50 325 inpatients from a large multicenter cohort (2014-2017). The authors separated patients from one hospital for external validation and randomly split the remaining patients into training and internal validation sets. A MARKov-EmbeDded (MARKED) multilabel model was proposed, and three models were trained for comparison: binary relevance, a fully connected network (FULLNET), and a deep neural network. Performance was mainly evaluated using the area under the receiver operating characteristic curve (AUC). The authors interpreted the model using Shapley Additive Explanations. Complication-specific risk and risk source inference were provided at the individual level. RESULTS: There were 26 292, 6574, and 17 459 inpatients in the training, internal validation, and external validation sets, respectively. For the external validation set, MARKED achieved the highest average AUC (0.818, 95% CI: 0.771-0.864) across eight outcomes [compared with binary relevance, 0.799 (0.748-0.849), FULLNET, 0.806 (0.756-0.856), and deep neural network, 0.815 (0.765-0.866)]. Specifically, the AUCs of MARKED were above 0.9 for cardiac complications [0.927 (0.894-0.960)], neurological complications [0.905 (0.870-0.941)], and mortality [0.902 (0.867-0.937)]. Serum albumin, surgical specialties, emergency case, American Society of Anesthesiologists score, age, and sex were the six most important preoperative variables. The interaction between complications contributed more than the preoperative variables, and formed a hierarchical chain of risk factors, mild complications, and severe complications. CONCLUSION: The authors demonstrated the advantage of MARKED in terms of performance and interpretability. The authors expect that the identification of high-risk patients and the inference of the risk source for specific complications will be valuable for clinical decision-making.

Patient attitudes, experiences, and satisfaction with healthcare and office visit utilization among Medicare beneficiaries with type 2 diabetes.

OBJECTIVES: To examine patient attitudes, experiences, and satisfaction with healthcare associated with office visit utilization among Medicare beneficiaries with type 2 diabetes. METHODS: We analyzed the 2019 Medicare Current Beneficiary Survey Public Use File of beneficiaries aged ≥65 years with type 2 diabetes (n = 1092). The ordinal dependent variable was defined as 0, 1 to 5, and ≥6 office visits. An ordinal partial proportional odds model was conducted to examine associations of beneficiaries' attitudes, experiences, and satisfaction with healthcare and office visit utilization. RESULTS: Among the beneficiaries, approximately 17.7%, 22.8%, and 59.5% reported having 0, 1 to 5, and ≥6 office visits, respectively. Being male (OR = 0.67, p = 0.004), Hispanic (OR = 0.53, p = 0.006), divorced/separated (OR = 0.62, p = 0.038) and living in a non-metro area (OR = 0.53, p < 0.001) were associated with a lower likelihood of attending more office visits. Trying to keep sickness to themselves (OR = 0.66, p = 0.002) and dissatisfaction with the ease and convenience of getting to providers from home (OR = 0.45, p = 0.010) were associated with a lower likelihood of having more office visits. DISCUSSION: The proportion of beneficiaries foregoing office visits is concerning. Attitudes concerning healthcare and transportation challenges can be barriers to office visits. Efforts to ensure timely and appropriate access to care should be prioritized for Medicare beneficiaries with diabetes.

Accessibility and Utilization of Telehealth Services During the COVID-19 Pandemic Among Medicare Beneficiaries by Diabetes Status.

Due to the influence types of telehealth services (i.e., phone and/or video) can have on patient care and outcomes, we sought to examine factors associated with the types of telehealth services offered and used among Medicare beneficiaries. We analyzed the Medicare Current Beneficiary Survey COVID-19 Public Use File (N = 1,403 and N = 2,218 for individuals with and without diabetes, respectively) and performed multinomial logit models to examine factors (e.g., sociodemographics, comorbidities, digital access/knowledge) associated with types of telehealth services offered and used among beneficiaries aged ≥65 years by diabetes status. Medicare beneficiaries seemed to prefer using telehealth via phone than video. Regardless of diabetes status, having not previously participated in video or voice calls or conferencing can be a barrier to telehealth being offered and used via video for beneficiaries. For older adults with diabetes, disparities in accessibility of telehealth via video by income and languages spoken other than English were observed. [Research in Gerontological Nursing, 16(3), 134-146.].

Clinical Utility of Strain Imaging in Assessment of Myocardial Fibrosis.

Myocardial fibrosis (MF) is a non-reversible process that occurs following acute or chronic myocardial damage. MF worsens myocardial deformation, remodels the heart and raises myocardial stiffness, and is a crucial pathological manifestation in patients with end-stage cardiovascular diseases and closely related to cardiac adverse events. Therefore, early quantitative analysis of MF plays an important role in risk stratification, clinical decision, and improvement in prognosis. With the advent and development of strain imaging modalities in recent years, MF may be detected early in cardiovascular diseases. This review summarizes the clinical usefulness of strain imaging techniques in the non-invasive assessment of MF.

Exploring density rectification and domain adaption method for crowd counting.

Crowd counting has received increasing attention due to its important roles in multiple fields, such as social security, commercial applications, epidemic prevention and control. To this end, we explore two critical issues that seriously affect the performance of crowd counting including nonuniform crowd density distribution and cross-domain problems. Aiming at the nonuniform crowd density distribution issue, we propose a density rectifying network (DRNet) that consists of several dual-layer pyramid fusion modules (DPFM) and a density rectification map (DRmap) auxiliary learning module. The proposed DPFM is embedded into DRNet to integrate multi-scale crowd density features through dual-layer pyramid fusion. The devised DRmap auxiliary learning module further rectifies the incorrect crowd density estimation by adaptively weighting the initial crowd density maps. With respect to the cross-domain issue, we develop a domain adaptation method of randomly cutting mixed dual-domain images, which learns domain-invariance features and decreases the domain gap between the source domain and the target domain from global and local perspectives. Experimental results indicate that the devised DRNet achieves the best mean absolute error (MAE) and competitive mean squared error (MSE) compared with other excellent methods on four benchmark datasets. Additionally, a series of cross-domain experiments are conducted to demonstrate the effectiveness of the proposed domain adaption method. Significantly, when the A and B parts of the Shanghaitech dataset are the source domain and target domain respectively, the proposed domain adaption method decreases the MAE of DRNet by 47.6 % .

Assessment of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in patients with high myopia.

BACKGROUND: Previous reports have suggested that inflammation levels play a crucial role in the pathogenesis of high myopia (HM). This study aimed to investigate the relationship between HM and systemic inflammation using the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR). METHODS: Overall, 100 age- and sex-matched participants were recruited for the study, including 50 participants each in the non-HM (NHM) and HM groups. Ocular examinations and blood tests were performed. The NLR and PLR values were calculated from complete blood counts. Receiver operating characteristic (ROC) curves and optimal cut-off values were used to determine the optimal values of the NLR and PLR to distinguish between the HM and NHM groups. RESULTS: The values of NLR and PLR were significantly elevated in the HM group compared with those in the NHM group (P < 0.001 and P = 0.010, respectively). Axial length (AL) was significantly correlated with the NLR (r = 0.367, P < 0.001) and PLR (r = 0.262, P = 0.009). In the ROC analysis, the NLR value to distinguish between the HM and NHM groups was 0.728; the best cut-off value was 2.68, with 76% sensitivity and 62% specificity. The PLR value to distinguish between the HM and NHM groups was 0.650; the best cut-off value was 139.69, with 52% sensitivity and 76% specificity. CONCLUSION: The findings of this study indicate that the development of HM may be associated with systemic inflammation measured using the NLR and PLR. TRIAL REGISTRATION: The study was registered on December 28, 2021 ( http://www.chictr.org.cn ; ChiCTR2100054834).

Analysis of Structural Health Monitoring Data with Correlated Measurement Error by Bayesian System Identification: Theory and Application.

Measurement error is non-negligible and crucial in SHM data analysis. In many applications of SHM, measurement errors are statistically correlated in space and/or in time for data from sensor networks. Existing works solely consider spatial correlation for measurement error. When both spatial and temporal correlation are considered simultaneously, the existing works collapse, as they do not possess a suitable form describing spatially and temporally correlated measurement error. In order to tackle this burden, this paper generalizes the form of correlated measurement error from spatial correlation only or temporal correlation only to spatial-temporal correlation. A new form of spatial-temporal correlation and the corresponding likelihood function are proposed, and multiple candidate model classes for the measurement error are constructed, including no correlation, spatial correlation, temporal correlation, and the proposed spatial-temporal correlation. Bayesian system identification is conducted to achieve not only the posterior probability density function (PDF) for the model parameters, but also the posterior probability of each candidate model class for selecting the most suitable/plausible model class for the measurement error. Examples are presented with applications to model updating and modal frequency prediction under varying environmental conditions, ensuring the necessity of considering correlated measurement error and the capability of the proposed Bayesian system identification in the uncertainty quantification at the parameter and model levels.

Assessment of macular structures and vascular characteristics in highly myopic anisometropia using swept-source optical coherence tomography angiography.

Purpose: This study aimed to explore the macular structures and vascular characteristics of more myopic (MM) and contralateral eyes with highly myopic anisometropia. Methods: Comprehensive ophthalmic examinations were performed for 33 patients with highly myopic anisometropia. Macular structures (total retinal layer [TRL], ganglion cell and inner plexiform layer [GCIPL], inner nuclear layer [INL], outer retinal layer [ORL], nerve fiber layer [NFL], choroidal layer [CHL]) and vascular characteristics (superficial vascular complex density [SVD], deep vascular complex density [DVD], choriocapillaris perfusion area [CCPA]) were assessed using swept-source optical coherence tomography (SS-OCT) and OCT angiography (OCTA). Macular structures and vascular characteristics of each subregion were compared to those of the Early Treatment of Diabetic Retinopathy Study (ETDRS). Results: With highly myopic anisometropia, the thicknesses of the TRL, GCIPL, INL, and ORL in MM eyes were smaller than those in contralateral eyes in at least one quadrant of the perifoveal and parafoveal circles (all p < 0.05), with no changes in the foveal and temporal quadrants of perifoveal regions (all p > 0.05). A thicker NFL (p = 0.018) was found in MM eyes than in contralateral eyes in the superior perifoveal quadrant. The CHL (all p < 0.05) in MM eyes was thinner in all regions than in the contralateral eyes according to the ETDRS. There were no statistical differences in the SVD, DVD, and CCPA of MM and contralateral eyes (all p > 0.05). Conclusion: All retinal layers, except the NFL, tended to be thinner in all subregions, except the temporal perifoveal and foveal quadrants in MM eyes, and choroidal thickness was thinned in all areas.

Critical assessment of protozoa contamination and control measures in mass culture of the diatom Phaeodactylum tricornutum.

The diatom Phaeodactylum tricornutum is considered a promising "cell factory" for high-value products fucoxanthin and EPA. But its potential has not been realized due largely to microbial contamination. In this study, seven protozoan strains were identified, of which a heterolobosean amoeba was identified as the most frequently occurring and destructive predator in P. tricornutum culture. The addition of 400 mg L-1 NH4HCO3 inhibited amoeba proliferation with little impact on algal growth. Halting culture mixing at night induced a hypoxia environment that further inhibited amoeba growth. Regardless of culture systems employed, a periodical supply of proper amounts of NH4HCO3 alone or in combination with halting culture mixing at night may prevent or treat protozoa contamination in mass culture of P. tricornutum.

Application of the Chinese Version of the Montreal Cognitive Assessment-Basic for Assessing Mild Cognitive Impairment in Parkinson's Disease.

Mild cognitive impairment (MCI) is a common and pivotal non-motor symptom in Parkinson's disease (PD). It is necessary to use the appropriate tools to characterize the cognitive profiles and identify the subjects at risk of MCI in clinical practice. A cohort of 207 non-demented patients with PD and 52 age- and gender-matched cognitively normal controls (NCs) underwent the Chinese Version of Montreal Cognitive Assessment-Basic (MoCA-BC) evaluation. Patients with PD also received detailed motor and non-motor evaluation by serial scales. Cognitive profiles were investigated in patients with PD-MCI, relative to patients with normal cognition (PD-NC) and cognitively NCs. In addition, differences in demography, major motor and non-motor symptoms were compared between patients with PD-MCI and PD-NC. There were 70 patients with PD-MCI, occupying 33.8% of the total patients. Patients with PD-MCI had impairment in multiple cognitive domains, especially in executive function, memory and visuospatial function on MoCA-BC, relative to cognitively NCs or PD-NC. Compared with PD-NC patients, PD-MCI patients were older (p = 0.002) and had a later onset age (p = 0.007) and higher score of the Unified Parkinson's Disease Rating Scale (UPDRS) part III (p = 0.001). The positive rate of clinical possible rapid eye movement sleep behavior disorder (cpRBD) in the PD-MCI group was significantly increased relative to the PD-NC group (p = 0.003). Multivariate logistic analysis showed that older age (OR = 1.06; p = 0.012), higher score of UPDRS-III (OR = 1.03; p = 0.018) and the presence of cpRBD (OR = 2.10; p = 0.037) were independently associated factors of MCI in patients with PD. In conclusion, executive function, memory and visuospatial function are the main impaired cognitive profiles in PD-MCI via MoCA-BC. Aging, motor severity and RBD may be independently related factors of MCI in PD.

Intelligent financial fraud detection practices in post-pandemic era.

The great losses caused by financial fraud have attracted continuous attention from academia, industry, and regulatory agencies. More concerning, the ongoing coronavirus pandemic (COVID-19) unexpectedly shocks the global financial system and accelerates the use of digital financial services, which brings new challenges in effective financial fraud detection. This paper provides a comprehensive overview of intelligent financial fraud detection practices. We analyze the new features of fraud risk caused by the pandemic and review the development of data types used in fraud detection practices from quantitative tabular data to various unstructured data. The evolution of methods in financial fraud detection is summarized, and the emerging Graph Neural Network methods in the post-pandemic era are discussed in particular. Finally, some of the key challenges and potential directions are proposed to provide inspiring information on intelligent financial fraud detection in the future.

Prescription drug coverage satisfaction, cost-reducing behavior, and medication nonadherence among Medicare beneficiaries with type 2 diabetes.

BACKGROUND: Medication nonadherence in individuals with type 2 diabetes can lead to poor glycemic control, resulting in increased risk for diabetes-related complications. OBJECTIVE: To examine associations between factors (ie, drug coverage satisfaction and cost-reducing behavior) and medication nonadherence among Medicare beneficiaries with type 2 diabetes. METHODS: We analyzed the 2016 Medicare Current Beneficiary Survey Public Use File for beneficiaries aged 65 years and older with reported type 2 diabetes (n=1,430; weighted n=5,846,943). Medicare beneficiaries were considered to have medication nonadherence if they reported skipping doses or taking smaller doses than prescribed. A survey-weighted logistic model, adjusted for sociodemographics and comorbidities, was conducted to examine associations of drug coverage satisfaction and cost-reducing behavior with medication nonadherence. RESULTS: Among Medicare beneficiaries aged 65 years and older with type 2 diabetes, 10.3% reported medication nonadherence. In the adjusted analysis, the risk for medication nonadherence was higher among those who were dissatisfied with the amount paid for medications (OR = 2.43; P = 0.002) compared with those who were satisfied, and those who spent less on basic needs to save for medications were more likely to report medication nonadherence (OR = 2.23; P = 0.011) than those who did not. CONCLUSIONS: Our findings suggest that medication nonadherence among Medicare beneficiaries with type 2 diabetes is associated with dissatisfaction with the amount paid for medications and cost-reducing behavior. Interventions that lower medication costs for Medicare beneficiaries may help to improve medication adherence among this at-risk population. DISCLOSURES: No outside funding supported this study. The authors have no conflicts of interest to disclose.

Assessment of a Novel Oleaginous Filamentous Microalga Klebsormidium sp. Lgx80 (Streptophyta, Klebsormidiales) for Biomass and Lipid Production1.

Commercial cultivation of eukaryotic microalgae has so far employed a unicellular form of species only (e.g., Chlorella pyrenoidosa, Dunaliella salina, and Haematococcus pluvialis). In this study, we assessed the feasibility of using the filamentous eukaryotic microalga Klebsormidium sp. LGX80 as a new cultivar for biomass and lipid production. The effects of different forms and concentrations of nitrogen on growth and lipid production of Klebsormidium sp. LGX80 were studied by using a glass column (ø4.5 × 60 cm) photobioreactor under laboratory conditions. Growth and lipid production of the new strain were further evaluated in an outdoor pilot-scale tubular photobioreactor. The results showed that when supplied with urea as a source of nitrogen Klebsormidium sp. LGX80 yielded a final biomass concentration of 8.49 ± 0.10 g · L-1 in which a cellular lipid content was 59.2 ± 0.4% DW. Under such conditions, the biomass and lipid productivities were 471.7 ± 5.9 and 248.1 ± 0.0 mg · L-1  · d-1 , respectively. Fatty acid analysis revealed that the main fatty acids of Klebsormidium sp. LGX80 were palmitic acid (C16:0), linoleic acid (C18:2ω6), and linolenic acid (C18:3ω3), of which linoleic acid (C18:2ω6) accounted for up to 67.5 ± 0.1% of total fatty acids. When grown outdoors in a 13,000-L tubular photobioreactor with an initial nitrogen concentration of 3 mM urea, Klebsormidium sp. LGX80 reached the highest biomass concentration of 2.63 ± 0.09 g · L-1 with the cells containing 38.0 ± 0.5% lipids (% DW), resulting in the volumetric biomass and lipid productivities of 147.2 ± 3.6 and 37.9 ± 0.9 mg · L-1  d-1 , respectively. The results of light:dark cycle experiment showed that a durative and prolonged light irradiation hindered the biosynthesis of chlorophyll a and chlorophyll b in the cells, but promoted the carotenoid accumulation. These results suggested that Klebsormidium sp. LGX80 can be a potential oleaginous filamentous microalga for commercial production of microalgal oils.

Active Enhancer Assessment by H3K27ac ChIP-seq Reveals Claudin-1 as a Biomarker for Radiation Resistance in Colorectal Cancer.

BACKGROUND: Colorectal cancer (CRC) represents the third most common malignant tumor in the worldwide. Radiotherapy is the common therapeutic treatment for CRC, but radiation resistance is often encountered. ChIP-seq of Histone H3K27 acetylation (H3K27ac) has revealed enhancers that play an important role in CRC. This study examined the relationship between an active CRC enhancer and claudin-1 (CLDN1), and its effect on CRC radiation resistance. METHODS: The target CRC genes of active enhancers were obtained from public H3K27ac ChIP-seq, and the genes highly expressed in radio-resistant CRC were screened and intersected with enhancer-driven genes. The clinical roles of CLDN1 in radiation resistance were examined using the t-test, standard mean deviation (SMD), summary receiver operating characteristic curve and Kaplan-Meier curves. The co-expressed genes of CLDN1 were calculated using Pearson Correlation analysis, and Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes and Gene Set Variation Analysis (GSVA) analyses were used to examine the molecular mechanisms of CLDN1. RESULTS: Total 13 703 CRC genes were regulated by enhancers using 58 H3K27ac ChIP-seq. Claudin-1 (CLDN1) was enhancer-driven and notably up-regulated in CRC tissues compared to non-CRC controls, with a SMD of 3.45 (95 CI % = .56-4.35). CLDN1 expression was increased in radiation-resistant CRC with a SMD of .42 (95% CI = .16-.68) and an area under the curve of .74 (95% CI = .70-.77). The cell cycle and immune macrophage levels were the most significant pathways associated with CLDN1. CONCLUSION: CLDN1 as an enhancer-regulated gene that can boost radiation resistance in patients with CRC.

Copula-Based Uncertainty Quantification (Copula-UQ) for Multi-Sensor Data in Structural Health Monitoring.

The problem of uncertainty quantification (UQ) for multi-sensor data is one of the main concerns in structural health monitoring (SHM). One important task is multivariate joint probability density function (PDF) modelling. Copula-based statistical inference has attracted significant attention due to the fact that it decouples inferences on the univariate marginal PDF of each random variable and the statistical dependence structure (called copula) among the random variables. This paper proposes the Copula-UQ, composing multivariate joint PDF modelling, inference on model class selection and parameter identification, and probabilistic prediction using incomplete information, for multi-sensor data measured from a SHM system. Multivariate joint PDF is modeled based on the univariate marginal PDFs and the copula. Inference is made by combing the idea of the inference functions for margins and the maximum likelihood estimate. Prediction on the PDF of the target variable, using the complete (from normal sensors) or incomplete information (due to missing data caused by sensor fault issue) of the predictor variable, are made based on the multivariate joint PDF. One example using simulated data and one example using temperature data of a multi-sensor of a monitored bridge are presented to illustrate the capability of the Copula-UQ in joint PDF modelling and target variable prediction.

Factors Associated With Avoiding Health Care Among Community-Dwelling Medicare Beneficiaries With Type 2 Diabetes.

INTRODUCTION: Health care avoidance by Medicare beneficiaries with chronic conditions such as type 2 diabetes can result in adverse health and economic outcomes. The objective of this study was to describe factors associated with choices to avoid health care among Medicare beneficiaries with type 2 diabetes. METHODS: We used a survey-weighted logistic model and the nationally representative 2016 Medicare Current Beneficiary Survey to analyze data on 1,782 Medicare beneficiaries aged ≥65 with type 2 diabetes, to examine associations between Medicare beneficiaries' decisions to avoid health care and multiple factors (eg, dissatisfaction with information given by providers, health problems that should have been discussed with providers but were not, worry about health more than other people their age). RESULTS: Of our study sample, 26.1% reported they avoid health care. Five factors were associated with avoiding health care: delaying care (vs not) because of costs (adjusted odds ratio [aOR] = 2.06; P = .005); having health problems that should have been discussed with providers but were not (vs having discussions) (aOR = 1.50; P = .04); worrying (vs not) about health more than other people their age (aOR = 2.13; P < .001); self-reporting "other" minority race (vs non-Hispanic White) (aOR = 2.01; P = .006); and education levels. Participants with less than a high school diploma (aOR = 1.95; P = .001) and participants with a high school diploma only (aOR = 1.49; P = .049) were more likely than participants with an education beyond high school to report avoiding health care. CONCLUSION: Approximately 1 in 4 Medicare beneficiaries with type 2 diabetes avoid health care. We found inequities in care-seeking behavior by race/ethnicity and education level. Health care perceptions and lack of appropriate discussion of health care concerns with health care providers are also associated with this behavior. Clinical interventions (eg, improved patient-provider communication) and educational outreach are needed to decrease the numbers of Medicare beneficiaries who avoid health care.

Biosynthetic Mycotoxin Conjugate Mimetics-Mediated Green Strategy for Multiplex Mycotoxin Immunochromatographic Assay.

Various mycotoxins widely co-exist in agro-products, and their combined effects cause toxicity and potential carcinogenicity to humans and animals. In this work, we developed an economical and sensitive quantum dots (QDs)/QD microbead (QDs/QB)-based multiplex immunochromatographic assay (mICA) for the rapid detection of fumonisin B1 (FB1), zearalenone (ZEN), and ochratoxin A (OTA) without the building-up process of mycotoxin conjugates. QDs and QBs were selected as fluorescent reporters and conjugated with antimycotoxin monoclonal antibodies for improving sensitivity. Furthermore, phage-displayed FB1, ZEN, and OTA mimotope peptide-based soluble and monovalent fusions to maltose-binding protein (MBP) were applied onto the test line of the mICA as the mimetic coating antigen. Under the optimized conditions, the visual detection limits (vLODs) of peptide-MBP-based mICA could be obtained as 0.25 ng/mL for FB1, 3.0 ng/mL for ZEN, and 0.5 ng/mL for OTA within 10 min. The results for spiked real sample detection indicate good accuracy, reproducibility, and practicability. In addition, the proposed mICA was comparable with ultraperformance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) in terms of reliability in detecting FB1, ZEN, and OTA using natural samples. From the point of promoting commercial production, these time-saving and low-cost peptide-MBP antigens applied in ICA might provide promising potential for promoting productivity and decreasing the cost of production.

[Diagnosis accuracy of quick sequential organ failure assessment score for adult sepsis patient with soft tissue infection].

OBJECTIVE: To assess the diagnosis accuracy of the quick sequential organ failure assessment (qSOFA) score for adult sepsis patient with soft tissue infection, and to assess the prognostic accuracy of the qSOFA score for septic shock. METHODS: A retrospective study was conducted. The patients with soft tissue infection admitted to the general surgery department of Beijing Hospital and the burns and plastic surgery department of Fourth Medical Center of PLA General Hospital from January 2012 to December 2018 were enrolled. Patients were divided into the sepsis group and the non-sepsis group according to whether sepsis occurred within 48 hours after diagnosis of infection. The baseline data, prognosis, and qSOFA, the change of sequential organ failure assessment (ΔSOFA), systemic inflammatory response syndrome (SIRS) scores were compared between the two groups, and the receiver operating characteristic (ROC) curves were also drawn to assess the diagnosis accuracy of the qSOFA and SIRS scores for adult sepsis patients with soft tissue infection and to assess the prognostic accuracy of the qSOFA, ΔSOFA and SIRS scores for septic shock of these patients. RESULTS: 192 patients were included in the study. Sepsis occurred in 79 patients (41.1%) within 48 hours after diagnosis of infection. Septic shock occurred in 28 patients (14.6%) during 28-day hospitalization and 6 patients (3.1%) died. Compared with non-sepsis group, more proportion of necrotizing fasciitis, septic shock and patients received mechanical ventilation (21.5% vs. 4.4%, 31.6% vs. 2.7%, 16.5% vs. 4.4%, all P < 0.01), with higher mortality (7.6% vs. 0%, P = 0.003) in sepsis group. ROC curve analysis showed that when the cut-off value of qSOFA ≥ 2, the sensitivity, specificity, positive predictive value, negative predictive value and area under ROC curve (AUC) were 48.1%, 92.0%, 80.8%, 71.7% and 0.824 [95% confidence interval (95%CI) = 0.764-0.884, P < 0.01] respectively for diagnosis of sepsis caused by soft tissue infection. When the cut-off value of SIRS score ≥ 3, the sensitivity, specificity, positive predictive value, negative predictive value and AUC were 89.8%, 48.6%, 55.0%, 87.3% and 0.721 (95%CI = 0.677-0.765, P < 0.01) respectively for diagnosis of sepsis caused by soft tissue infection. All scores of qSOFA ≥ 2, ΔSOFA ≥ 2 and SIRS score ≥ 3 could be used to predict septic shock (all P < 0.01). The AUC of ΔSOFA, qSOFA and SIRS scores were 0.767 (95%CI = 0.665-0.869), 0.840 (95%CI = 0.757-0.923) and 0.716 (95%CI = 0.596-0.835) respectively. CONCLUSIONS: qSOFA ≥ 2 can be used as a rapid sepsis screening tool for adult patients with soft tissue infection. It is suggested that qSOFA or SIRS scores can be used to predict septic shock of adult patients with soft tissue infection initially.

Assessment of liver regeneration after associating liver partition and portal vein ligation for staged hepatectomy: a comparative study with portal vein ligation.

BACKGROUND: To investigate the diagnostic value of diffusion kurtosis imaging (DKI) and diffusion-weighted imaging (DWI) in assessing liver regeneration after associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) compared with portal vein ligation (PVL). METHODS: Thirty rats were divided into the ALPPS, PVL, and control groups. DKI and DWI were performed before and 7 days after surgery. Corrected apparent diffusion (D), kurtosis (K) and apparent diffusion coefficient (ADC) were calculated and compared, radiologic-pathologic correlations were evaluated. RESULTS: The volume of the right median lobe increased significantly after ALPPS. There were larger cellular diameters after ALPPS and PVL (P = 0.0003). The proliferative indexes of Ki-67 and hepatocyte growth factor were higher after ALPPS (P = 0.0024/0.0433). D, K and ADC values differed between the groups (P = 0.021/0.0015/0.0008). A significant correlation existed between D and the hepatocyte size (r = -0.523), no correlations existed in ADC and K (P = 0.159/0.111). The proliferative indexes showed moderate negative correlations with ADC (r = -0.484/-0.537) and no correlations with D and K (P = 0.100-0.877). DISCUSSION: Liver regeneration after ALPPS was effective and superior to PVL. DKI, especially the D map, may provide added value in evaluating the microstructure of liver regeneration after ALPPS, but this model alone may perform no better than the standard monoexponential model of DWI.