Functional vascularization is critical for the clinical regeneration of complex tissues such as kidney, liver or bone. The immobilization or delivery of growth factors has been explored to improve vascularization capacity of tissue engineered constructs, however, the use of growth factors has inherent problems such as the loss of signaling capability and the risk of complications such as immunological responses and cancer. Here, a new method of preparing water-insoluble silk protein scaffolds with vascularization capacity using an all aqueous process is reported. Acid was added temporally to tune the self-assembly of silk in lyophilization process, resulting in water insoluble scaffold formation directly. These biomaterials are mainly noncrystalline, offering improved cell proliferation than previously reported silk materials. These systems also have appropriate softer mechanical property that could provide physical cues to promote cell differentiation into endothelial cells, and enhance neovascularization and tissue ingrowth in vivo without the addition of growth factors. Therefore, silk-based degradable scaffolds represent an exciting biomaterial option, with vascularization capacity for soft tissue engineering and regenerative medicine.

Diabetes is one of common endocrine and metabolic disorder diseases, and it leads to multiple complications causing uncountable suffering and incalculable economic losses to worldwide patients. 1 Globally, the number of people with diabetes mellitus has quadrupled in the past three decades. About 1 in 11 adults now have diabetes mellitus, and 90% of them are type 2 diabetes. 2 Diabetes has increasingly become a global problem to be solved urgently.

Background: Breast imaging technology plays an important role in breast cancer planning and treatment. Recently, three-dimensional (3D) printing technology has become a trending issue in phantom constructions for medical applications, with its advantages of being customizable and cost-efficient. However, there is no current practice in the field of multipurpose breast phantom for quality control (QC) in multi-modalities imaging. The purpose of this study was to fabricate a multipurpose breast phantom with tissue-equivalent materials via a 3D printing technique for QC in multi-modalities imaging. Methods: We used polyvinyl chloride (PVC) based materials and a 3D printing technique to construct a breast phantom. The phantom incorporates structures imaged in the female breast such as microcalcifications, fiber lesions, and tumors with different sizes. Moreover, the phantom was used to assess the sensitivity of lesion detection, depth resolution, and detectability thresholds with different imaging modalities. Phantom tissue equivalent properties were determined using computed tomography (CT) attenuation [Hounsfield unit (HU)] and magnetic resonance imaging (MRI) relaxation times. Results: The 3D-printed breast phantom had an average background value of 36.2 HU, which is close to that of glandular breast tissue (40 HU). T1 and T2 relaxation times had an average relaxation time of 206.81±17.50 and 20.22±5.74 ms, respectively. Mammographic imaging had improved detection of microcalcification compared with ultrasound and MRI with multiple sequences [T1WI, T2WI and short inversion time inversion recovery (STIR)]. Soft-tissue lesion detection and cylindrical tumor contrast were superior with mammography and MRI compared to ultrasound. Hemispherical tumor detection was similar regardless of the imaging modality used. Conclusions: We developed a multipurpose breast phantom using a 3D printing technique and determined its value for multi-modal breast imaging studies.

Objective: Cancer stem cell marker CD44 and its variant isoforms (CD44v) may be correlated with tumor growth, metastasis, and chemo-radiotherapy resistance. However, the prognostic power of CD44 and CD44v in advanced cancer remains controversial. Therefore, the purpose of our study was to generalize the prognostic significance of these cancer stem cell markers in advanced cancer patients.Methods: Hazard ratios (HRs) with 95% confidence intervals (95% CIs) were calculated from multivariable analysis to assess the associations among CD44, CD44v6, and CD44v9 positivity and overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), cancer-specific survival (CSS), and recurrence-free survival (RFS). Trial sequential analysis (TSA) was also conducted.Results: We included 15 articles that reported on 1,201 patients with advanced cancer (CD44: nine studies with 796 cases, CD44v6: three studies with 143 cases, and CD44v9: three studies with 262 cases). CD44 expression was slightly linked to worse OS (HR = 2.03, P = 0.027), but there was no correlation between CD44 expression and DFS, RFS, or PFS. Stratified analysis showed that CD44 expression was not correlated with OS at ≥5 years or OS in patients receiving adjuvant therapy. CD44v6 expression was not associated with OS. CD44v9 expression was closely associated with poor 5-years CSS in patients treated with chemo/radiotherapy (HR = 3.62, P < 0.001). However, TSA suggested that additional trials were needed to confirm these conclusions.Conclusions: CD44 or CD44v9 might be novel therapeutic targets for improving the treatment of advanced cancer patients. Additional prospective clinical trials are strongly needed across different cancer types.

The purpose of this study was to establish the one-repetition maximum (1RM) prediction equations of a biceps curl, bench press, and squat from the submaximal skeletal muscle strength of 4-10RM or 11-15RM in older adults. The first group of 109 participants aged 60-75 years was recruited to measure their 1RM, 4-10RM, and 11-15RM of the three exercises. The 1RM prediction equations were developed by multiple regression analyses. A second group of participants with similar physical characteristics to the first group was used to evaluate the equations. The actual measured 1RM of the second group correlated significantly to the predicted 1RM obtained from the equations (r values were from .633-.985), and standard error of estimate ranged from 1.08-5.88. Therefore, the equations can be used to predict 1RM from submaximal skeletal muscle strength accurately for older adults.Keywords: muscle strength, one repetition maximum, submaximal strength, prediction equation, older adults.Skeletal muscle strength is very important to the well-being of older adults. Previous studies have reported that skeletal muscle strength and mass gradually decline during the aging process (Delmonico et al., 2009; Frontera, Hughes, Lutz, & Evans, 1991; Gallagher et al., 1997;Janssen, Heymsfield, Wang, & Ross, 2000;Lindle et al., 1997). This geriatric syndrome has been defined as sarcopenia, which may increase the risks of falls, fractures, disabilities, and loss of independence in older adults (Cruz-Jentoft et al., 2010). Furthermore, low skeletal muscle strength is considered as one of the major factors of poor quality of life as people get older (Imagama et al., 2011; Samuel, Rowe, Hood, & Nicol, 2012). To manage this geriatric health problem, resistance exercise has been applied to maintain or improve skeletal muscle strength for older adults (Peterson, Rhea, Sen, & Gordon, 2010). However, to design the most effective resistance training program and achieve the most benefits from this intervention, we need to measure the skeletal muscle strength accurately at baseline to clarify the initial situation of the skeletal muscles, determine the suitable resistance training intensity, and evaluate the potential effects following resistance training.One-repetition maximum (1RM) is the standard for dynamic skeletal muscle strength assessment (American College of Sports Medicine, 2006, pp. 80-83). As it is defined, 1RM tests require participants to perform with maximum effort during testing, and it usually takes many trials and a long time to reach the 1RM. Even though this test has been reported as an acceptable tool to apply to older adults (Barnard, Adams, Swank, Mann, & Marty, 1999; Shaw, McCully, & Posner, 1995), the high physical stress during the test may still pose a risk for the participants, such as incurring muscle or bone injuries, particularly for those who have low physical fitness and are physically inactive. Therefore, prediction of 1RM from submaximal efforts would be an alternative test which is safer and time efficient. In the...

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Purpose This study aimed to establish an animal model in which we can precisely displace the spinal cord and therefore mimic the chronic spinal compression of cervical spondylotic myelopathy. Methods In vivo intervertebral compression devices (IVCDs) connected with subcutaneous control modules (SCCMs) were implanted into the C2-3 intervertebral disk spaces of sheep and connected by Bluetooth to an in vitro control system. Sixteen sheep were divided into four groups: (Group A) control; (Group B) 10-week progressive compression, then held; (Group C) 20-week progressive compression, then held; and (Group D) 20-week progressive compression, then decompression. Electrophysiological analysis (latency and amplitude of the N1-P1-N2 wave in somatosensory evoked potentials, SEP), behavioral changes (Tarlov score), imaging test (encroachment ratio (ER) of intraspinal invasion determined by X-ray and CT scan), and histological examinations (hematoxylin and eosin, Nissl, and TUNEL staining) were performed to assess the efficacy of our model. Results Tarlov scores gradually decreased as compression increased with time and partially recovered after decompression. The Pearson correlation coefficient between ER and time was r = 0.993 (p < 0.001) in Group B at 10 weeks and Groups C and D at 20 weeks. And ER was negatively correlated with the Tarlov score (r = -0.878, p < 0.001). As compression progressed, the SEP latency was significantly extended (p < 0.001), and the amplitude significantly decreased (p < 0.001), while they were both partially restored after decompression. The number of abnormal motor neurons and TUNEL-positive cells increased significantly (p < 0.001) with compression. Conclusion Our implantable and wireless intervertebral compression model demonstrated outstanding controllability and reproducibility in simulating chronic cervical spinal cord compression in animals.

Objective. To evaluate the value of pulmonary bedside ultrasound system in the assessment of severity and prognosis of acute lung injury (ALI). Method. Seventy-two ALI patients in the intensive care unit (ICU) of our hospital from April 2019 to April 2021 were selected as subjects. The changes of lung ultrasound score (LUS) and parameters at D1, D2, and D3 after admission were analyzed (LUS, oxygenation index (PaO2/FiO2), Acute Physiology and Chronic Health Evaluation II (APACHE-II), and Sequential Organ Failure Assessment (SOFA) score). Pearson correlation analysis was used to assess the relationship between LUS and PaO2/FiO2, APACHE-II score, and SOFA score at D1, D2, and D3. Logistic regression analysis was used for influencing factors for the prognosis of ALI patients. Receiver operating characteristic (ROC) curve was used to analyze the predictive value of baseline LUS, PaO2/FiO2, APACHE-II score, and SOFA score for the prognosis of ALI patients. Result. LUSs at D1, D2 and D3 showed an increasing trend with the increase of disease severity ( P < 0.05 ). From D1 to D3, LUS, PaO2/FiO2, APACHE-II score, and SOFA score showed a downward trend ( P < 0.05 ). LUS was negatively correlated with PaO2/FiO2 at D1, D2, and D3 but positively correlated with APACHE-II score and SOFA score ( P < 0.05 ). Logistic regression analysis showed that after controlling for age, PaO2 and PaCO2, an increase in baseline LUS, APACHE-II score, SOFA score, and a decrease in PaO2/FiO2 were independent risk factors for death at 28 d in ALI patients ( P < 0.05 ). ROC curve showed that LUS, PaO2/FiO2, APACHE-II score, and SOFA score were combined to predict the prognosis of ALI patients with the highest AUC value of 0.920, corresponding sensitivity of 88.89%, and specificity of 95.56%. Conclusion. LUS can evaluate the change of pulmonary ventilation area in ALI patients, further evaluate the severity of the disease, and effectively predict the prognosis of patients.