Proteomic profiles of peritoneal fluid-derived small extracellular vesicles correlate with patient outcome in ovarian cancer.

Cancer-derived small extracellular vesicles (sEVs) are capable of modifying the tumor microenvironment and promoting tumor progression. Ovarian cancer (OvCa) is a lethal malignancy that preferentially spreads through the abdominal cavity. Thus, the secretion of such vesicles into the peritoneal fluid could be a determinant factor in the dissemination and behavior of this disease. We designed a prospective observational study to assess the impact of peritoneal fluid-derived sEVs (PFD-sEVs) in OvCa clinical outcome. For this purpose, 2 patient cohorts were enrolled: patients with OvCa who underwent a diagnostic or cytoreductive surgery and nononcological patients, who underwent abdominal surgery for benign gynecological conditions and acted as the control group. Systematic extraction of PFD-sEVs from surgical samples enabled us to observe significant quantitative and qualitative differences associated with cancer diagnosis, disease stage, and platinum chemosensitivity. Proteomic profiling of PFD-sEVs led to the identification of molecular pathways and proteins of interest and to the biological validation of S100A4 and STX5. In addition, unsupervised analysis of PFD-sEV proteomic profiles in high-grade serous ovarian carcinomas (HGSOCs) revealed 2 clusters with different outcomes in terms of overall survival. In conclusion, comprehensive characterization of PFD-sEV content provided a prognostic value with potential implications in HGSOC clinical management.

Case-control study assessing the impact of COVID19 in advanced kidney cancer patients treated with antiangiogenics or immunotherapy: the COVID-REN study.

BACKGROUND: Cancer is a risk factor for developing severe COVID19. Additionally, SARS-CoV2 has a special tropism for renal cells and complications like thrombosis or cytokine storm could be enhanced by standard treatments in kidney cancer (i.e., antiangiogenics or immunotherapy). Thus, understanding the impact of COVID19 in patients with this tumor is key for their correct management. METHODS: We designed a retrospective case-control study comparing the outcome of three groups of advanced kidney cancer patients on systemic treatment: cohort A (developed COVID19 while on antiangiogenics), cohort B (developed COVID19 while on immunotherapy) and cohort C (non-infected). Matching factors were age, gender, and treatment. RESULTS: 95 patients were recruited in 16 centers in Spain from September 2020 to May 2021. Finally, 85 were deemed as eligible (23 cohort A, 21 cohort B, 41 cohort C). Patients with COVID required more dose interruptions (25 vs. six) and hospitalizations (10 vs. none) than those without COVID (both p = 0.001). No difference between cohorts A and B was observed regarding hospitalization or length of stay. No ICU admission was registered and one patient in cohort B died due to COVID19. Regarding cancer evolution, three patients in cohort A presented progressive disease after COVID19 compared to two in cohort B. One case in cohort B, initially deemed as stable disease, achieved a partial response after COVID19. CONCLUSIONS: Kidney cancer patients who developed COVID19 while on systemic therapy required more treatment interruptions and hospitalizations than those non-infected. However, no significant impact on cancer outcome was observed. Also, no difference was seen between cases on antiangiogenics or immunotherapy.

Randomized phase II clinical trial of ruxolitinib plus simvastatin in COVID19 clinical outcome and cytokine evolution.

Background: Managing the inflammatory response to SARS-Cov-2 could prevent respiratory insufficiency. Cytokine profiles could identify cases at risk of severe disease. Methods: We designed a randomized phase II clinical trial to determine whether the combination of ruxolitinib (5 mg twice a day for 7 days followed by 10 mg BID for 7 days) plus simvastatin (40 mg once a day for 14 days), could reduce the incidence of respiratory insufficiency in COVID-19. 48 cytokines were correlated with clinical outcome. Participants: Patients admitted due to COVID-19 infection with mild disease. Results: Up to 92 were included. Mean age was 64 ± 17, and 28 (30%) were female. 11 (22%) patients in the control arm and 6 (12%) in the experimental arm reached an OSCI grade of 5 or higher (p = 0.29). Unsupervised analysis of cytokines detected two clusters (CL-1 and CL-2). CL-1 presented a higher risk of clinical deterioration vs CL-2 (13 [33%] vs 2 [6%] cases, p = 0.009) and death (5 [11%] vs 0 cases, p = 0.059). Supervised Machine Learning (ML) analysis led to a model that predicted patient deterioration 48h before occurrence with a 85% accuracy. Conclusions: Ruxolitinib plus simvastatin did not impact the outcome of COVID-19. Cytokine profiling identified patients at risk of severe COVID-19 and predicted clinical deterioration. Trial registration: https://clinicaltrials.gov/, identifier NCT04348695.

Early detection of anthracycline- and trastuzumab-induced cardiotoxicity: value and optimal timing of serum biomarkers and echocardiographic parameters.

AIMS: To evaluate echocardiographic and biomarker changes during chemotherapy, assess their ability to early detect and predict cardiotoxicity and to define the best time for their evaluation. METHODS AND RESULTS: Seventy-two women with breast cancer (52 ± 9.8 years) treated with anthracyclines (26 also with trastuzumab), were evaluated for 14 months (6 echocardiograms/12 laboratory tests). We analysed: high-sensitivity cardiac troponin T, NT-proBNP, global longitudinal strain (GLS), left ventricle end-systolic volume (LVESV), left ventricle end-diastolic volume (LVEDV), and left ventricular ejection fraction (LVEF). Cardiotoxicity was defined as a reduction in LVEF>10% compared with baseline with LVEF<53%. High-sensitivity troponin T levels rose gradually reaching a maximum peak at 96 ± 13 days after starting chemotherapy (P < 0.001) and 62.5% of patients presented increased values during treatment. NT-proBNP augmented after each anthracycline cycle (mean pre-cycle levels of 72 ± 68 pg/mL and post-cycle levels of 260 ± 187 pg/mL; P < 0.0001). Cardiotoxicity was detected in 9.7% of patients (mean onset at 5.2 months). In the group with cardiotoxicity, the LVESV was higher compared with those without cardiotoxicity (40 mL vs. 29.5 mL; P = 0.045) at 1 month post-anthracycline treatment and the decline in GLS was more pronounced (-17.6% vs. -21.4%; P = 0.03). Trastuzumab did not alter serum biomarkers, but it was associated with an increase in LVESV and LVEDV (P < 0.05). While baseline LVEF was an independent predictor of later cardiotoxicity (P = 0.039), LVESV and GLS resulted to be early detectors of cardiotoxicity [odds ratio = 1.12 (1.02-1.24), odds ratio = 0.66 (0.44-0.92), P < 0.05] at 1 month post-anthracycline treatment. Neither high-sensitivity troponin T nor NT-proBNP was capable of predicting subsequent cardiotoxicity. CONCLUSIONS: One month after completion of anthracycline treatment is the optimal time to detect cardiotoxicity by means of imaging parameters (LVESV and GSL) and to determine maximal troponin rise. Baseline LVEF was a predictor of later cardiotoxicity. Trastuzumab therapy does not affect troponin values hence imaging techniques are recommended to detect trastuzumab-induced cardiotoxicity.

Behavioural immune landscapes of inflammation.

Transcriptional and proteomic profiling of individual cells have revolutionized interpretation of biological phenomena by providing cellular landscapes of healthy and diseased tissues1,2. These approaches, however, do not describe dynamic scenarios in which cells continuously change their biochemical properties and downstream 'behavioural' outputs3-5. Here we used 4D live imaging to record tens to hundreds of morpho-kinetic parameters describing the dynamics of individual leukocytes at sites of active inflammation. By analysing more than 100,000 reconstructions of cell shapes and tracks over time, we obtained behavioural descriptors of individual cells and used these high-dimensional datasets to build behavioural landscapes. These landscapes recognized leukocyte identities in the inflamed skin and trachea, and uncovered a continuum of neutrophil states inside blood vessels, including a large, sessile state that was embraced by the underlying endothelium and associated with pathogenic inflammation. Behavioural screening in 24 mouse mutants identified the kinase Fgr as a driver of this pathogenic state, and interference with Fgr protected mice from inflammatory injury. Thus, behavioural landscapes report distinct properties of dynamic environments at high cellular resolution.

Application of pelvic floor ultrasound during pregnancy to detect patients at risk of cesarean section due to failure of labor progression in a Spanish population.

OBJECTIVE: Our study is aimed at evaluating the characteristics of the pelvic floor, assessed through transperineal ultrasound, since it may influence or increase the possibility of having a cesarean delivery, with the objective of acting on those variables that can be modified during pregnancy. STUDY DESIGN: Transperineal ultrasound was performed on 109 primiparous pregnant women in their first trimester of pregnancy, recruited between May 2018 and February 2019, with the purpose of studying the hiatus area at rest, retention and Valsalva. We have reassessed them at the end of pregnancy and delivery data were recorded. We selected 8 patients as case-study, who had cesarean section delivery due to failure of labor progression. We selected 4 control-cases for each, reaching the total of 32 controls, with similar age and body mass index, to avoid obtaining a biased result from these data. RESULTS: In the study of hiatal areas, patients who delivered by cesarean section had a smaller hiatal area at rest, during levator ani muscle contraction and during Valsalva maneuver, at all visits. In early pregnancy, the range of the resting hiatal area was 13.8 ± 2.0 cm2 for cesarean sections, compared to 16.2 ± 2.7 cm2 for vaginal deliveries with an OR of 0.57 (0.34-0.95, 95% CI). For hiatal area on Valsalva, the OR was 0.55 (0.35-0.88, 95% CI). Therefore, the smaller the hiatal area, the greater the possibility of cesarean section. At the end of pregnancy, between 34 and 36 weeks of gestation, the OR of hiatal area on Valsalva was 0.78 (0.60-1.00, 95% CI). CONCLUSION: The hiatus area measured by transperineal ultrasonography at the beginning and at the end of the pregnancy may be useful to identify the patients who are at a higher risk of cesarean delivery due to failure of labor progression.

Unravelling glioblastoma heterogeneity by means of single-cell RNA sequencing.

Glioblastoma (GBM) is the most invasive and deadliest brain cancer in adults. Its inherent heterogeneity has been designated as the main cause of treatment failure. Thus, a deeper understanding of the diversity that shapes GBM pathobiology is of utmost importance. Single-cell RNA sequencing (scRNA-seq) technologies have begun to uncover the hidden composition of complex tumor ecosystems. Herein, a semi-systematic search of reference literature databases provided all existing publications using scRNA-seq for the investigation of human GBM. We compared and discussed findings from these works to build a more robust and unified knowledge base. All aspects ranging from inter-patient heterogeneity to intra-tumoral organization, cancer stem cell diversity, clonal mosaicism, and the tumor microenvironment (TME) are comprehensively covered in this report. Tumor composition not only differs across patients but also involves a great extent of heterogeneity within itself. Spatial and cellular heterogeneity can reveal tumor evolution dynamics. In addition, the discovery of distinct cell phenotypes might lead to the development of targeted treatment approaches. In conclusion, scRNA-seq expands our knowledge of GBM heterogeneity and helps to unravel putative therapeutic targets.

Hemogram-derived ratios as prognostic markers of ICU admission in COVID-19.

BACKGROUND: The vast impact of COVID-19 call for the identification of clinical parameter that can help predict a torpid evolution. Among these, endothelial injury has been proposed as one of the main pathophysiological mechanisms underlying the disease, promoting a hyperinflammatory and prothrombotic state leading to worse clinical outcomes. Leukocytes and platelets play a key role in inflammation and thrombogenesis, hence the objective of the current study was to study whether neutrophil-to-lymphocyte ratio (NLR), platelets-to-lymphocyte ratio (PLR), the systemic immune-inflammation index (SII) as well as the new parameter neutrophil-to-platelet ratio (NPR), could help identify patients who at risk of admission at Intensive Care Units. METHODS: A retrospective observational study was performed at HM Hospitales including electronic health records from 2245 patients admitted due to COVID-19 from March 1 to June 10, 2020. Patients were divided into two groups, admitted at ICU or not. RESULTS: Patients who were admitted at the ICU had significantly higher values in all hemogram-derived ratios at the moment of hospital admission compared to those who did not need ICU admission. Specifically, we found significant differences in NLR (6.9 [4-11.7] vs 4.1 [2.6-7.6], p <  0.0001), PLR (2 [1.4-3.3] vs 1.9 [1.3-2.9], p = 0.023), NPR (3 [2.1-4.2] vs 2.3 [1.6-3.2], p <  0.0001) and SII (13 [6.5-25.7] vs 9 [4.9-17.5], p <  0.0001) compared to those who did not require ICU admission. After multivariable logistic regression models, NPR was the hemogram-derived ratio with the highest predictive value of ICU admission, (OR 1.11 (95% CI: 0.98-1.22, p = 0.055). CONCLUSIONS: Simple, hemogram-derived ratios obtained from early hemogram at hospital admission, especially the novelty NPR, have shown to be useful predictors of risk of ICU admission in patients hospitalized due to COVID-19.

kinetics of anti-SARS-CoV-2 antibodies over time. Results of 10 month follow up in over 300 seropositive Health Care Workers.

BACKGROUND: The kinetics of the antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) needs to be evaluated since long-term duration of antibody remains largely unknown, particularly in infected healthcare workers (HCW). METHODS: Prospective study, evaluating the longitudinal profile of anti-SARS-CoV-2 antibody titers in a random sample of 331 seropositive healthcare workers (HCW) of Spanish Hospitals Group. Serial measurements of serum IgG-anti-SARS-CoV-2 were obtained at baseline (April-May,2020), and in 2 follow-up visits. Linear mixed models were used to investigate antibody kinetics and associated factors. RESULTS: A total of 306 seropositive subjects (median age: 44.7years;69.9% female) were included in the final analysis. After a median follow-up of 274 days between baseline and final measurement, 235(76.8%) maintained seropositivity. Antibody titers decreased in 82.0%, while remained stable in 13.1%. Factors associated with stability of antibodies over time included age≥45 years, higher baseline titers, severe/moderate infection and high-grade exposure to COVID-19 patients. In declining profile, estimated mean antibody half-life was 146.3 days(95%CI:138.6-154.9) from baseline. Multivariate models show independent longer durability of antibodies in HCW with high-risk exposure to COVID-19 patients (+14.1 days;95%CI:0.6-40.2) and with symptomatic COVID-19 (+14.1 days;95%CI:0.9-43.0). The estimated mean time to loss antibodies was 375(95% CI:342-408) days from baseline. CONCLUSIONS: We present the first study measuring the kinetics of antibody response against SARS-CoV-2 in HCW beyond 6 months. Most participants remained seropositive after 9 months but presented a significant decline in antibody-titers. Two distinct antibody dynamic profiles were observed (declining vs. stable). Independent factors associated with longer durability of antibodies were symptomatic infection and higher exposure to COVID-19 patients.

Hemogram as marker of in-hospital mortality in COVID-19.

The clinical impact of COVID-19 disease calls for the identification of routine variables to identify patients at increased risk of death. Current understanding of moderate-to-severe COVID-19 pathophysiology points toward an underlying cytokine release driving a hyperinflammatory and procoagulant state. In this scenario, white blood cells and platelets play a direct role as effectors of such inflammation and thrombotic response. We investigate whether hemogram-derived ratios such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio and the systemic immune-inflammation index may help to identify patients at risk of fatal outcomes. Activated platelets and neutrophils may be playing a decisive role during the thromboinflammatory phase of COVID-19 so, in addition, we introduce and validate a novel marker, the neutrophil-to-platelet ratio (NPR).Two thousand and eighty-eight hospitalized patients with COVID-19 admitted at any of the hospitals of HM Hospitales group in Spain, from March 1 to June 10, 2020, were categorized according to the primary outcome of in-hospital death.Baseline values, as well as the rate of increase of the four ratios analyzed were significantly higher at hospital admission in patients who died than in those who were discharged (p<0.0001). In multivariable logistic regression models, NLR (OR 1.05; 95% CI 1.02 to 1.08, p=0.00035) and NPR (OR 1.23; 95% CI 1.12 to 1.36, p<0.0001) were significantly and independently associated with in-hospital mortality.According to our results, hemogram-derived ratios obtained at hospital admission, as well as the rate of change during hospitalization, may easily detect, primarily using NLR and the novel NPR, patients with COVID-19 at high risk of in-hospital mortality.

Risk Score for Predicting In-Hospital Mortality in COVID-19 (RIM Score).

Infection by SARS-CoV2 has devastating consequences on health care systems. It is a global health priority to identify patients at risk of fatal outcomes. 1955 patients admitted to HM-Hospitales from 1 March to 10 June 2020 due to COVID-19, were were divided into two groups, 1310 belonged to the training cohort and 645 to validation cohort. Four different models were generated to predict in-hospital mortality. Following variables were included: age, sex, oxygen saturation, level of C-reactive-protein, neutrophil-to-platelet-ratio (NPR), neutrophil-to-lymphocyte-ratio (NLR) and the rate of changes of both hemogram ratios (VNLR and VNPR) during the first week after admission. The accuracy of the models in predicting in-hospital mortality were evaluated using the area under the receiver-operator-characteristic curve (AUC). AUC for models including NLR and NPR performed similarly in both cohorts: NLR 0.873 (95% CI: 0.849-0.898), NPR 0.875 (95% CI: 0.851-0.899) in training cohort and NLR 0.856 (95% CI: 0.818-0.895), NPR 0.863 (95% CI: 0.826-0.901) in validation cohort. AUC was 0.885 (95% CI: 0.885-0.919) for VNLR and 0.891 (95% CI: 0.861-0.922) for VNPR in the validation cohort. According to our results, models are useful in predicting in-hospital mortality risk due to COVID-19. The RIM Score proposed is a simple, widely available tool that can help identify patients at risk of fatal outcomes.

Beyond the Warburg Effect: Oxidative and Glycolytic Phenotypes Coexist within the Metabolic Heterogeneity of Glioblastoma.

Glioblastoma (GBM) is the most aggressive primary brain tumor, with a median survival at diagnosis of 16-20 months. Metabolism represents a new attractive therapeutic target; however, due to high intratumoral heterogeneity, the application of metabolic drugs in GBM is challenging. We characterized the basal bioenergetic metabolism and antiproliferative potential of metformin (MF), dichloroacetate (DCA), sodium oxamate (SOD) and diazo-5-oxo-L-norleucine (DON) in three distinct glioma stem cells (GSCs) (GBM18, GBM27, GBM38), as well as U87MG. GBM27, a highly oxidative cell line, was the most resistant to all treatments, except DON. GBM18 and GBM38, Warburg-like GSCs, were sensitive to MF and DCA, respectively. Resistance to DON was not correlated with basal metabolic phenotypes. In combinatory experiments, radiomimetic bleomycin exhibited therapeutically relevant synergistic effects with MF, DCA and DON in GBM27 and DON in all other cell lines. MF and DCA shifted the metabolism of treated cells towards glycolysis or oxidation, respectively. DON consistently decreased total ATP production. Our study highlights the need for a better characterization of GBM from a metabolic perspective. Metabolic therapy should focus on both glycolytic and oxidative subpopulations of GSCs.

Seroprevalence of SARS-CoV-2 antibodies in over 6000 healthcare workers in Spain.

BACKGROUND: Spain has one of the highest incidences of coronavirus disease 2019 (COVID-19) worldwide, so Spanish health care workers (HCW) are at high risk of exposure. Our objective was to determine severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody seroprevalence amongst HCW and factors associated with seropositivity. METHODS: A cross-sectional study evaluating 6190 workers (97.8% of the total workforce of a healthcare-system of 17 hospitals across four regions in Spain) was carried out between April and June 2020, by measuring immunoglobulin G (IgG)-SARS-CoV-2 antibody titres and related clinical data. Exposure risk was categorized as high (clinical environment; prolonged/direct contact with patients), moderate (clinical environment; non-intense/no patient contact) and low (non-clinical environment). RESULTS: A total of 6038 employees (mean age 43.8 years; 71% female) were included in the final analysis. A total of 662 (11.0%) were seropositive for IgG against SARS-CoV-2 (39.4% asymptomatic). Adding available PCR-testing, 713 (11.8%) employees showed evidence of previous SARS-CoV-2 infection. However, before antibody testing, 482 of them (67%) had no previous diagnosis of SARS-CoV-2-infection. Seroprevalence was higher in high- and moderate-risk exposure (12.1 and 11.4%, respectively) compared with low-grade risk subjects (7.2%), and in Madrid (13.8%) compared with Barcelona (7.6%) and Coruña (2.0%). High-risk [odds ratio (OR): 2.06; 95% confidence interval (CI): 1.63-2.62] and moderate-risk (OR: 1.77; 95% CI: 1.32-2.37) exposures were associated with positive IgG-SARS-CoV-2 antibodies after adjusting for region, age and sex. Higher antibody titres were observed in moderate-severe disease (median antibody-titre: 13.7 AU/mL) compared with mild (6.4 AU/mL) and asymptomatic (5.1 AU/mL) infection, and also in older (>60 years: 11.8 AU/mL) compared with younger (<30 years: 4.2 AU/mL) people. CONCLUSIONS: Seroprevalence of IgG-SARS-CoV-2 antibodies in HCW is a little higher than in the general population and varies depending on regional COVID-19 incidence. The high rates of subclinical and previously undiagnosed infection observed in this study reinforce the utility of antibody screening. An occupational risk for SARS-CoV-2 infection related to working in a clinical environment was demonstrated in this HCW cohort.

Normal tissue content impact on the GBM molecular classification.

Molecular classification of glioblastoma has enabled a deeper understanding of the disease. The four-subtype model (including Proneural, Classical, Mesenchymal and Neural) has been replaced by a model that discards the Neural subtype, found to be associated with samples with a high content of normal tissue. These samples can be misclassified preventing biological and clinical insights into the different tumor subtypes from coming to light. In this work, we present a model that tackles both the molecular classification of samples and discrimination of those with a high content of normal cells. We performed a transcriptomic in silico analysis on glioblastoma (GBM) samples (n = 810) and tested different criteria to optimize the number of genes needed for molecular classification. We used gene expression of normal brain samples (n = 555) to design an additional gene signature to detect samples with a high normal tissue content. Microdissection samples of different structures within GBM (n = 122) have been used to validate the final model. Finally, the model was tested in a cohort of 43 patients and confirmed by histology. Based on the expression of 20 genes, our model is able to discriminate samples with a high content of normal tissue and to classify the remaining ones. We have shown that taking into consideration normal cells can prevent errors in the classification and the subsequent misinterpretation of the results. Moreover, considering only samples with a low content of normal cells, we found an association between the complexity of the samples and survival for the three molecular subtypes.

Newcastle Disease Virus (NDV) Oncolytic Activity in Human Glioma Tumors Is Dependent on CDKN2A-Type I IFN Gene Cluster Codeletion.

Glioblastoma (GBM) is the most aggressive and frequent primary brain tumor in adults with a median overall survival of 15 months. Tumor recurrence and poor prognosis are related to cancer stem cells (CSCs), which drive resistance to therapies. A common characteristic in GBM is CDKN2A gene loss, located close to the cluster of type I IFN genes at Ch9p21. Newcastle disease virus (NDV) is an avian paramyxovirus with oncolytic and immunostimulatory properties that has been proposed for the treatment of GBM. We have analyzed the CDKN2A-IFN I gene cluster in 1018 glioma tumors and evaluated the NDV oncolytic effect in six GBM CSCs ex vivo and in a mouse model. Our results indicate that more than 50% of GBM patients have some IFN deletion. Moreover, GBM susceptibility to NDV is dependent on the loss of the type I IFN. Infection of GBM with an NDV-expressing influenza virus NS1 protein can overcome the resistance to oncolysis by NDV of type I-competent cells. These results highlight the potential of using NDV vectors in antitumor therapies.

BRAF V600E Detection in Liquid Biopsies from Pediatric Central Nervous System Tumors.

Pediatric Central Nervous System (CNS) tumors are the most fatal cancer diseases in childhood. Due to their localization and infiltrative nature, some tumor resections or biopsies are not feasible. In those cases, the use of minimally invasive methods as diagnostic, molecular marker detection, prognostic or monitoring therapies are emerging. The analysis of liquid biopsies which contain genetic information from the tumor has been much more widely explored in adults than in children. We compare the detection of BRAF V600E targetable mutation by digital-PCR from cell-free-DNA and EV-derived DNA (ctDNA) in serum, plasma and cerebrospinal fluid (CSF) isolated from a cohort of 29 CNS pediatric patients. Here we demonstrate that ctDNA isolated from serum and plasma could be successfully analyzed to obtain tumor genetic information which could be used to guide critical treatment decisions.

Emergence of supercontraction in regenerated silkworm (Bombyx mori) silk fibers.

The conditions required for the emergence of supercontraction in regenerated silkworm (Bombyx mori) silk fibers are assessed through an experimental approach that combines the spinning of regenerated fibers with controlled properties and their characterization by 13C solid-state nuclear magnetic resonance (NMR). Both supercontracting and non-supercontracting regenerated fibers are produced using the straining flow spinning (SFS) technique from 13C labeled cocoons. The short-range microstructure of the fibers is assessed through 13C CP/MAS in air and 13C DD/MAS in water, and the main microstructural features are identified and quantified. The mechanical properties of the regenerated fibers and their microstructures are compared with those of natural silkworm silk. The combined analysis highlights two possible key elements as responsible for the emergence of supercontraction: (1) the existence of an upper and a lower limit of the amorphous phase compatible with supercontraction, and (2) the existence of two ordered phases, ß-sheet A and B, which correspond to different packing arrangements of the protein chains.

Influence of medium viscosity and intracellular environment on the magnetization of superparamagnetic nanoparticles in silk fibroin solutions and 3T3 mouse fibroblast cell cultures.

Biomedical applications based on the magnetic properties of superparamagnetic iron oxide nanoparticles (SPIONs) may be altered by the mechanical attachment or cellular uptake of these nanoparticles. When nanoparticles interact with living cells, they are captured and internalized into intracellular compartments. Consequently, the magnetic behavior of the nanoparticles is modified. In this paper, we investigated the change in the magnetic response of 14 nm magnetic nanoparticles (Fe3O4) in different solutions, both as a stable liquid suspension (one of them mimicking the cellular cytoplasm) and when associated with cells. The field-dependent magnetization curves from inert fluids and cell cultures were determined by using an alternating gradient magnetometer, MicroMagTM 2900. The equipment was adapted to measure liquid samples because it was originally designed only for solids. In order to achieve this goal, custom sample holders were manufactured. Likewise, the nuclear magnetic relaxation dispersion profiles for the inert fluid were also measured by fast field cycling nuclear magnetic relaxation relaxometry. The results show that SPION magnetization in inert fluids was affected by the carrier liquid viscosity and the concentration. In cell cultures, the mechanical attachment or confinement of the SPIONs inside the cells accounted for the change in the dynamic magnetic behavior of the nanoparticles. Nevertheless, the magnetization value in the cell cultures was slightly lower than that of the fluid simulating the viscosity of cytoplasm, suggesting that magnetization loss was not only due to medium viscosity but also to a reduction in the mechanical degrees of freedom of SPIONs rotation and translation inside cells. The findings presented here provide information on the loss of magnetic properties when nanoparticles are suspended in viscous fluids or internalized in cells. This information could be exploited to improve biomedical applications based on magnetic properties such as magnetic hyperthermia, contrast agents and drug delivery.

Straining Flow Spinning of Artificial Silk Fibers: A Review.

This work summarizes the main principles and some of the most significant results of straining flow spinning (SFS), a technology developed originally by the authors of this work. The principles on which the technology is based, inspired by the natural spinning system of silkworms and spiders, are presented, as well as some of the main achievements of the technique. Among these achievements, spinning under environmentally friendly conditions, obtaining high-performance fibers, and imparting the fibers with emerging properties such as supercontraction are discussed. Consequently, SFS appears as an efficient process that may represent one of the first realizations of a biomimetic technology with a significant impact at the production level.

Production of High Performance Bioinspired Silk Fibers by Straining Flow Spinning.

In the last years, there has been an increasing interest in bioinspired approaches for different applications, including the spinning of high performance silk fibers. Bioinspired spinning is based on the natural spinning system of spiders and worms and requires combining changes in the chemical environment of the proteins with the application of mechanical stresses. Here we present the novel straining flow spinning (SFS) process and prove its ability to produce high performance fibers under mild, environmentally friendly conditions, from aqueous protein dopes. SFS is shown to be an extremely versatile technique which allows controlling a large number of processing parameters. This ample set of parameters allows fine-tuning the microstructure and mechanical behavior of the fibers, which opens the possibility of adapting the fibers to their intended uses.