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Abstract Establishing prediction models of pregnancy outcomes for recurrent pregnancy loss women at specific gestational weeks will provide patients and physicians with more precise information, ultimately leading to time and cost savings associated with unnecessary revisits. Therefore, our aim was to develop a prediction model for first trimester pregnancy loss in RPL patients. We used ultrasound indices during the first trimester of pregnancy in combination with demographic characteristics and commonly used serum markers. The independent risk factors for each week were as follows: age and P in the fifth week; age, mGSD and CRL in the sixth week; age, hCG and CRL in the seventh week; CRL in the eighth week; mGSD and CRL in ninth week. The corresponding AUC was 0.671, 0.796, 0.872, 0.871, 0.813, respectively. There is a linear relationship between age and first trimester pregnancy loss. hCG 48.3 mm in ninth gestational week was associated with a higher risk of pregnancy loss. These models and thresholds may help physicians and patients make more informed decisions together. Further studies are needed to confirm the results.

Abstract Traumatic brain injury (TBI) is one of the leading causes of death and disability worldwide. However, effective diagnostic, therapeutic and prognostic biomarkers are still lacking. Our research group previously revealed through high-throughput sequencing that the serum exosomes miR-133a-3p, miR-206, and miR-549a-3p differ significantly in severe TBI (sTBI), mild or moderate TBI (mTBI), and control groups. However, convincing experimental evidence is lacking. To solve this problem, we used qPCR in this study to further verify the expression levels of serum exosomes miR-133a-3p, miR-206 and miR-549a-3p in TBI patients. The results showed that the serum exosomes miR-206 and miR-549a-3p showed good predictive value as biomarkers of TBI. In addition, in order to further verify whether serum exosomes miR-206 and miR-549a-3p can be used as potential biomarkers in patients with TBI and to understand the mechanism of their possible effects, we further determined the contents of SOD, BDNF, VEGF, VEGI, NSE and S100β in the serum of TBI patients. The results showed that, serum exosomes miR-206 and miR-549a-3p showed good correlation with BDNF, NSE and S100β. In conclusion, serum exosomes miR-206 and miR-549a-3p have the potential to serve as potential biomarkers in patients with TBI.

Abstract Osteoporosis is a major public health concern that significantly increases the risk of fractures. The aim of this study was to develop a Machine Learning based predictive model to screen individuals at high risk of osteoporosis based on chronic disease data, thus facilitating early detection and personalized management. A total of 10,000 complete patient records of primary healthcare data in the German Disease Analyzer database (IMS HEALTH) were included, of which 1293 diagnosed with osteoporosis and 8707 without the condition. The demographic characteristics and chronic disease data, including age, gender, lipid disorder, cancer, COPD, hypertension, heart failure, CHD, diabetes, chronic kidney disease, and stroke were collected from electronic health records. Ten different machine learning algorithms were employed to construct the predictive mode. The performance of the model was further validated and the relative importance of features in the model was analyzed. Out of the ten machine learning algorithms, the Stacker model based on Logistic Regression, AdaBoost Classifier, and Gradient Boosting Classifier demonstrated superior performance. The Stacker model demonstrated excellent performance through ten-fold cross-validation on the training set and ROC curve analysis on the test set. The confusion matrix, lift curve and calibration curves indicated that the Stacker model had optimal clinical utility. Further analysis on feature importance highlighted age, gender, lipid metabolism disorders, cancer, and COPD as the top five influential variables. In this study, a predictive model for osteoporosis based on chronic disease data was developed using machine learning. The model shows great potential in early detection and risk stratification of osteoporosis, ultimately facilitating personalized prevention and management strategies.

Abstract To investigate the biomechanical properties of posterior cruciate ligament avulsion fractures of the tibia fixed using four different methods, including triple tibial channel net suture fixation. In 40 porcine knees, a standardized bony avulsion of the posterior cruciate ligament was generated. Double tibial bone channel suture fixation was performed in group A, double-head hollow compression screw fixation was performed in group B, triple tibial bone channel net suture fixation was performed in group C, and cortical suspension EndoButton fixation was performed in group D. The constructs were cyclically loaded 500 times (10 to 100 N) to measure the initial displacement and stiffness values. Subsequently, loading to failure was performed, and the yield load and peak load were measured. The results were analysed by one-way ANOVA, with significance set at P

Abstract The primary function of heat shock transcription factor (HSF) in the heat shock response is to activate the transcription of genes encoding heat shock proteins (HSPs). The phloem-feeding insect Bemisia tabaci (Gennadius) is an important pest of cotton, vegetables and ornamentals that transmits several plant viruses and causes enormous agricultural losses. In this study, the gene encoding HSF (Bthsf1) was characterized in MED B. tabaci. The full-length cDNA encoded a protein of 652 amino acids with an isoelectric point of 5.55. The BtHSF1 deduced amino acid sequence showed strong similarity to HSF in other insects. Expression analyses using quantitative real-time PCR indicated that Bthsf1 was significantly up-regulated in B. tabaci adults and pupae during thermal stress. Although Bthsf1 was induced by both hot and cold stress, the amplitude of expression was greater in the former. Bthsf1 had distinct, significant differences in expression pattern during different duration of high but not low temperature stress. Oral ingestion of dsBthsf1 repressed the expression of Bthsf1 and four heat shock proteins (Bthsp90, Bthsp70-3, Bthsp20 and Bthsp19.5) in MED B. tabaci during hot and cold stress. In conclusion, our results show that Bthsf1 is differentially expressed during high and low temperature stress and regulates the transcription of multiple hsps in MED B. tabaci.

Abstract Quenching of vibrational excitations in resonant inelastic X-ray scattering (RIXS) spectra of liquid acetic acid is observed. At the oxygen core resonance associated with localized excitations at the O–H bond, the spectra lack the typical progression of vibrational excitations observed in RIXS spectra of comparable systems. We interpret this phenomenon as due to strong rehybridization of the unoccupied molecular orbitals as a result of hydrogen bonding, which however cannot be observed in x-ray absorption but only by means of RIXS. This allows us to address the molecular structure of the liquid, and to determine a lower limit for the average molecular chain length.