Plasma cell-free DNA promise monitoring and tissue injury assessment of COVID-19.

Coronavirus 2019 (COVID-19) is a complex disease that affects billions of people worldwide. Currently, effective etiological treatment of COVID-19 is still lacking; COVID-19 also causes damages to various organs that affects therapeutics and mortality of the patients. Surveillance of the treatment responses and organ injury assessment of COVID-19 patients are of high clinical value. In this study, we investigated the characteristic fragmentation patterns and explored the potential in tissue injury assessment of plasma cell-free DNA in COVID-19 patients. Through recruitment of 37 COVID-19 patients, 32 controls and analysis of 208 blood samples upon diagnosis and during treatment, we report gross abnormalities in cfDNA of COVID-19 patients, including elevated GC content, altered molecule size and end motif patterns. More importantly, such cfDNA fragmentation characteristics reflect patient-specific physiological changes during treatment. Further analysis on cfDNA tissue-of-origin tracing reveals frequent tissue injuries in COVID-19 patients, which is supported by clinical diagnoses. Hence, our work demonstrates and extends the translational merit of cfDNA fragmentation pattern as valuable analyte for effective treatment monitoring, as well as tissue injury assessment in COVID-19.

Application of machine learning model to predict osteoporosis based on abdominal computed tomography images of the psoas muscle: a retrospective study.

BACKGROUND: With rapid economic development, the world's average life expectancy is increasing, leading to the increasing prevalence of osteoporosis worldwide. However, due to the complexity and high cost of dual-energy x-ray absorptiometry (DXA) examination, DXA has not been widely used to diagnose osteoporosis. In addition, studies have shown that the psoas index measured at the third lumbar spine (L3) level is closely related to bone mineral density (BMD) and has an excellent predictive effect on osteoporosis. Therefore, this study developed a variety of machine learning (ML) models based on psoas muscle tissue at the L3 level of unenhanced abdominal computed tomography (CT) to predict osteoporosis. METHODS: Medical professionals collected the CT images and the clinical characteristics data of patients over 40 years old who underwent DXA and abdominal CT examination in the Second Affiliated Hospital of Wenzhou Medical University database from January 2017 to January 2021. Using 3D Slicer software based on horizontal CT images of the L3, the specialist delineated three layers of the region of interest (ROI) along the bilateral psoas muscle edges. The PyRadiomics package in Python was used to extract the features of ROI. Then Mann-Whitney U test and the least absolute shrinkage and selection operator (LASSO) algorithm were used to reduce the dimension of the extracted features. Finally, six machine learning models, Gaussian naïve Bayes (GNB), random forest (RF), logistic regression (LR), support vector machines (SVM), Gradient boosting machine (GBM), and Extreme gradient boosting (XGBoost), were applied to train and validate these features to predict osteoporosis. RESULTS: A total of 172 participants met the inclusion and exclusion criteria for the study. 82 participants were enrolled in the osteoporosis group, and 90 were in the non-osteoporosis group. Moreover, the two groups had no significant differences in age, BMI, sex, smoking, drinking, hypertension, and diabetes. Besides, 826 radiomic features were obtained from unenhanced abdominal CT images of osteoporotic and non-osteoporotic patients. Five hundred fifty radiomic features were screened out of 826 by the Mann-Whitney U test. Finally, 16 significant radiomic features were obtained by the LASSO algorithm. These 16 radiomic features were incorporated into six traditional machine learning models (GBM, GNB, LR, RF, SVM, and XGB). All six machine learning models could predict osteoporosis well in the validation set, with the area under the receiver operating characteristic (AUROC) values greater than or equal to 0.8. GBM is more effective in predicting osteoporosis, whose AUROC was 0.86, sensitivity 0.70, specificity 0.92, and accuracy 0.81 in validation sets. CONCLUSION: We developed six machine learning models to predict osteoporosis based on psoas muscle images of abdominal CT, and the GBM model had the best predictive performance. GBM model can better help clinicians to diagnose osteoporosis and provide timely anti-osteoporosis treatment for patients. In the future, the research team will strive to include participants from multiple institutions to conduct external validation of the ML model of this study.

Network pharmacology assessment of Qingkailing injection treatment of cholestatic hepatitis.

OBJECTIVE: To investigate the targets and mechanisms of action of Qingkailing injection (，QKL) in the treatment of cholestatic hepatitis. METHODS: A network pharmacology method was implemented using drug and disease databases to target QKL and cholestasis hepatitis, respectively. The functional protein association network STRING database was used to construct a protein-protein interaction network using R language and the Bioconductor toolkit. The org.Hs.eg.db and clusterProfiler packages were used for gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, which explored biological functions and pathways of potential targets. Targets were then visualized using Cytoscape 3.6.0 software. RESULTS: We screened 121 compounds in QKL and identified 112 targets for the treatment of cholestatic hepatitis. QKL played a role in the treatment of cholestatic hepatitis through 305 biology process terms, 15 cellular component and 29 molecular function terms. The mechanism of QKL action was mainly related to tumor necrosis factor, mitogen-activated protein kinase, and PI3K-Akt signaling pathways. CONCLUSION: The treatment of cholestatic hepatitis by QKL involved multiple targets, biological functions, and signaling pathways that are closely associated with the disease.

Efficient genome-wide first-generation phenotypic screening system in mice using the piggyBac transposon.

Genome-wide phenotypic screens provide an unbiased way to identify genes involved in particular biological traits, and have been widely used in lower model organisms. However, cost and time have limited the utility of such screens to address biological and disease questions in mammals. Here we report a highly efficient piggyBac (PB) transposon-based first-generation (F1) dominant screening system in mice that enables an individual investigator to conduct a genome-wide phenotypic screen within a year with fewer than 300 cages. The PB screening system uses visually trackable transposons to induce both gain- and loss-of-function mutations and generates genome-wide distributed new insertions in more than 55% of F1 progeny. Using this system, we successfully conducted a pilot F1 screen and identified 5 growth retardation mutations. One of these mutants, a Six1/4 PB/+ mutant, revealed a role in milk intake behavior. The mutant animals exhibit abnormalities in nipple recognition and milk ingestion, as well as developmental defects in cranial nerves V, IX, and X. This PB F1 screening system offers individual laboratories unprecedented opportunities to conduct affordable genome-wide phenotypic screens for deciphering the genetic basis of mammalian biology and disease pathogenesis.

Resting energy expenditure: a valuable predictor for KT/Vurea in peritoneal dialysis patients
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OBJECTIVE: The objective of this study was to identify an effective method for predicting small-molecule solute removal at the commencement of or before peritoneal dialysis (PD). METHODS: The PD patients with a dialysis delivery of 8 L/d and a residual kidney function (RKF) ≤ 5 mL/min were enrolled in the study. Fat-free lean body mass (FFM) and resting energy expenditure (REE) were measured using bioelectrical impedance (BIA). A receiver operating characteristic (ROC) curve was drawn to determine the threshold value for REE. The patients were divided into two groups, group A (lower REE) and group B (higher REE), based on their REE value. RESULTS: In total, 164 PD patients were enrolled between April 2013 and February 2015. REE was positively correlated with serum creatinine (Scr), blood urea nitrogen (BUN), blood uric acid (UA), body mass index (BMI), and body surface area (BSA) and negatively correlated with total KT/Vurea (KT/V) and hemoglobin (Hb). REE (HR = 0.987, 95% CI = 0.975 - 1.000, p = 0.044) was the only predictor for KT/V. When REE was less than 1469.2 kal/d, it was easier to achieve the target KT/V. The patients in group B had significantly larger body size than those in group A; however, Hb level and total KT/V for group B were significantly lower than those for group A. CONCLUSION: REE may be a helpful indicator for choosing a suitable dialysis modality for patients with end-stage renal disease (ESRD) and for improving the prognosis after PD.
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Raman spectrum: A potential biomarker for embryo assessment during in vitro fertilization.

The aim of the study was to investigate whether Raman spectrum is consistent with the morphological scoring of the embryo of day 3 during in vitro fertilization (IVF). The spent culture media of embryo of day 3 from 10 patients were collected and analyzed. The samples were analyzed using Raman spectroscopy and graded according to the standard embryo scoring system simultaneously. Data showed that the Raman spectra obtained from the droplet of media were useful, as they can act as the characteristic signature for protein and amino acids. The Raman biospectroscopy-based metabonomics profiling of spent media was consistent with the result of conventional morphological evaluation. In conclusion, this technology offers great potential for the development of tools allowing rapid non-invasive assessment of the quality of embryo of day 3 during IVF.

Optical coherence tomography assessment of a complex bifurcation lesion treated with double kissing Crush technique: A case report.

The DEFINITION (Impact of the complexity of bifurcation lesions treated with drug-eluting stents) study has provided a novel classification to evaluate the complexity of coronary bifurcation lesion according to coronary angiography, but angiographic imaging due to its low resolution and inherited limitation may result in an inaccurate adjudication.We used optical coherence tomography (OCT) to further evaluate the coronary characteristics in a patient with "simple" bifurcation lesion which was classified by the DEFINITION criteria. However, a "complex" bifurcation lesion was defined and confirmed according to the OCT results.A double kissing Crush stenting approach was adopted to treat this "complex" case finally. The immediate and long-term angiographic and OCT results were excellent.OCT may be useful imaging modality to classify complexity of coronary bifurcation lesion and subsequently guide its treatment strategy.

Impacts of low socioeconomic status and polycyclic aromatic hydrocarbons exposure on lung function among a community-based Chinese population.

Lung function is related to socioeconomic status (SES) and exposure to polycyclic aromatic hydrocarbons (PAHs). However, joint effect of SES and exposure to PAHs on lung function has been largely unknown. We aimed to investigate joint effects of SES and urinary OH-PAHs levels on lung function parameters. This study included 2739 Wuhan participants from the baseline survey of the Wuhan-Zhuhai (WHZH) Cohort Study (n=3053). They completed the questionnaire, physical examination and provided blood and urine samples. Twelve urinary monohydroxy-PAHs metabolites (OH-PAHs) and lung function were measured by gas chromatography-mass spectrometry and digital spirometers, respectively. Individuals with low educational levels and low or high levels of urinary ΣOH-PAHs had a 3.5% (95% CI: -5.4, -1.6%) or 4.2% (95% CI: -6.1, -2.3%) reduction in the ratio of forced expiratory volume in 1s to forced vital capacity (FEV1/FVC), respectively, and those with middle levels of education and high levels of urinary ΣOH-PAHs had a 2.1% (95% CI: -5.4, -1.6%) reduction in the FEV1/FVC ratio, rather than those with high levels of education and low levels of urinary ΣOH-PAHs. Individuals with low levels of education had a -3.0% (95% CI: -4.4, -1.6%) reduction in FEV1/FVC compared with individuals with high levels of education. Urinary OH-PAHs levels were marginally negatively related to FEV1 in all participants (p=0.073). The results indicated that there was a prominent effect of low levels of education and higher exposure to PAHs on lung function decline, indicating that it is a necessary to take measures to promote the education level and reduce exposure to environmental PAHs.

A smartphone-centric system for the range of motion assessment in stroke patients.

The range of motion (ROM) in stroke patients is often severely affected. Poststroke rehabilitation is guided through the use of clinical assessment scales for the rROM. Unfortunately, these scales are not widely utilized in clinical practice as they are excessively time-consuming. Although commercial motion-capture systems are capable of providing the information required for the assessments, most systems are either too costly or lack the convenience required for assessments to be conducted on a daily basis. This paper presents the design and implementation of a smartphone-based system for automated motor assessment using low-cost off-the-shelf inertial sensors. The system was used to automate a portion of the upper-extremity Fugl-Meyer assessment (FMA), which is widely used to quantify motor deficits in stroke survivors. Twelve out of 33 items were selected, focusing mainly on joint angle measurements of the upper body. The system has the ability to automatically identify the assessment item being conducted, and calculate the maximum respective joint angle achieved. Preliminary results show the ability of this system to achieve comparable results to goniometer measurements, while significantly reducing the time required to conduct the assessments. The portability and ease-of-use of the system would simplify the task of conducting range-of-motion assessments.

Reliability assessment and correlation analysis of evaluating orthodontic treatment outcome in Chinese patients.

This study aimed to assess the reliability of experienced Chinese orthodontists in evaluating treatment outcome and to determine the correlations between three diagnostic information sources. Sixty-nine experienced Chinese orthodontic specialists each evaluated the outcome of orthodontic treatment of 108 Chinese patients. Three different information sources: study casts (SC), lateral cephalometric X-ray images (LX) and facial photographs (PH) were generated at the end of treatment for 108 patients selected randomly from six orthodontic treatment centers throughout China. Six different assessments of treatment outcome were made by each orthodontist using data from the three information sources separately and in combination. Each assessment included both ranking and grading for each patient. The rankings of each of the 69 judges for the 108 patients were correlated with the rankings of each of the other judges yielding 13 873 Spearman rs values, ranging from -0.08 to +0.85. Of these, 90% were greater than 0.4, showing moderate-to-high consistency among the 69 orthodontists. In the combined evaluations, study casts were the most significant predictive component (R(2)=0.86, P<0.000 1), while the inclusion of lateral cephalometric films and facial photographs also contributed to a more comprehensive assessment (R(2)=0.96, P<0.000 1). Grading scores for SC+LX and SC+PH were highly significantly correlated with those for SC+LX+PH (r(SC+LX)vs.(SC+LX+PH)=0.96, r(SC+PH)vs.(SC+LX+PH)=0.97), showing that either SC+LX or SC+PH is an excellent substitute for all three combined assessment.

A novel dimeric thymosin beta 4 with enhanced activities accelerates the rate of wound healing.

OBJECTIVE: Thymosin beta 4 (Tß4) is a peptide with 43 amino acids that is critical for repair and remodeling tissues on the skin, eye, heart, and neural system following injury. To fully realize its utility as a treatment for disease caused by injury, the authors constructed a cost-effective novel Tß4 dimer and demonstrated that it was better able to accelerate tissue repair than native Tß4. METHODS: A prokaryotic vector harboring two complete Tß4 genes with a short linker was constructed and expressed in Escherichia coli. A pilot-scale fermentation (10 L) was performed to produce engineered bacteria and the Tß4 dimer was purified by one-step hydrophobic interaction chromatography. The activities of the Tß4 dimer to promote endothelial cell proliferation, migration, and sprouting were assessed by tetramethylbenzidine (methylthiazol tetrazolium), trans-well, scratch, and tube formation assays. The ability to accelerate dermal healing was assessed on rats. RESULTS: After fermentation, the Tß4 dimer accounted for about 30% of all the bacteria proteins. The purity of the Tß4 dimer reached 98% after hydrophobic interaction chromatography purification. An average of 562.4 mg/L Tß4 dimer was acquired using a 10 L fermenter. In each assay, the dimeric Tß4 exhibited enhanced activities compared with native Tß4. Notably, the ability of the dimeric Tß4 to promote cell migration was almost two times higher than that of Tß4. The rate of dermal healing in the dimeric Tß4-treated rats was approximately 1 day faster than with native Tß4-treated rats. CONCLUSION: The dimeric Tß4 exhibited enhanced activity on wound healing than native Tß4, and the purification process was simple and cost-effective. This data could be of significant benefit for the high pain and morbidity associated with chronic wounds disease. A better strategy to develop Tß4 as a treatment for other diseases caused by injuries such as heart attack, neurotrophic keratitis, and multiple sclerosis was also described.

Quantitative cervical vertebral maturation assessment in adolescents with normal occlusion: a mixed longitudinal study.

INTRODUCTION: The purpose of this study was to establish a quantitative cervical vertebral maturation (CVM) system for adolescents with normal occlusion. METHODS: Mixed longitudinal data were used. The subjects included 87 children and adolescents from 8 to 18 years old with normal occlusion (32 boys, 55 girls) selected from 901 candidates. Sequential lateral cephalograms and hand-wrist films were taken once a year for 6 years. The lateral cephalograms of all subjects were divided into 11 maturation groups according to the Fishman skeletal maturity indicators. The morphologic characteristics of the second, third, and fourth cervical vertebrae at 11 developmental stages were measured and analyzed. RESULTS: Three characteristic parameters (H4/W4, AH3/PH3, @2) were selected to determine the classification of CVM. With 3 morphologic variables, the quantitative CVM system including 4 maturational stages was established. An equation that can accurately estimate the maturation of the cervical vertebrae was established: CVM stage=-4.13+3.57xH4/W4+4.07xAH3/PH3+0.03x@2. CONCLUSIONS: The quantitative CVM method is an efficient, objective, and relatively simple approach to assess the level of skeletal maturation during adolescence.