Chronic wounds in diabetic patients are challenging because their prolonged inflammation makes healing difficult, thus burdening patients, society, and health care systems. Customized dressing ...materials are needed to effectively treat such wounds that vary in shape and depth. The continuous development of 3D‐printing technology along with artificial intelligence has increased the precision, versatility, and compatibility of various materials, thus providing the considerable potential to meet the abovementioned needs. Herein, functional 3D‐printing inks comprising DNA from salmon sperm and DNA‐induced biosilica inspired by marine sponges, are developed for the machine learning‐based 3D‐printing of wound dressings. The DNA and biomineralized silica are incorporated into hydrogel inks in a fast, facile manner. The 3D‐printed wound dressing thus generates provided appropriate porosity, characterized by effective exudate and blood absorption at wound sites, and mechanical tunability indicated by good shape fidelity and printability during optimized 3D printing. Moreover, the DNA and biomineralized silica act as nanotherapeutics, enhancing the biological activity of the dressings in terms of reactive oxygen species scavenging, angiogenesis, and anti‐inflammation activity, thereby accelerating acute and diabetic wound healing. These bioinspired 3D‐printed hydrogels produce using a DNA‐induced biomineralization strategy are an excellent functional platform for clinical applications in acute and chronic wound repair.
The healing of chronic wounds in diabetic patients is challenging due to prolonged inflammation. In this study, bioinspired 3D printing inks comprising of functionalized sodium alginate (FSA), biomineralized silica, and DNA are developed. Bioinspired hydrogel dressings fabricated with DNA‐bSi@FSA inks and the 3D printing process are optimized using machine learning. The potential of using biomineralization‐based nanotherapeutics for chronic wound repair is evaluated.
In vascular surgical applications, small-diameter vascular grafts made from synthetic polymers are rarely commercialized, owing to delayed reendothelialization and subsequent thrombus formation and ...occlusion. Here, we describe a novel design for a small-diameter poly-ε-caprolactone (PCL) vascular graft with a functional, bilayered nanofibrous structure and a composition that enables a suitable healing process and gradual degradation/replacement by natural blood vessels. To improve vascular cell responses to the PCL, a natural bioactive polymer (collagen) and a sol–gel-derived bioceramic (silica) were incorporated into the inner and outer layer of the PCL vascular graft, respectively. An electrospinning technique enabled the development of uniform electrospun PCL/collagen and PCL/silica nanofibers. In particular, the orientations of PCL/collagen nanofibers prepared with a high-speed rotating collector were highly aligned, and no breaks or irregular shapes were observed. The thin inner layer, composed of PCL/collagen with longitudinally aligned nanofibers, was favorable for the adhesion, elongation, and migration of endothelial cells, thus eliciting rapid reendothelialization of luminal surfaces of a vascular graft. The relatively thick outer layer, composed of PCL/silica with randomly distributed nanofibers, provided a superior mechanical strength and showed satisfactory biocompatibility. The findings of this study demonstrate a strong potential of PCL-based bilayer vascular grafts for vascular tissue applications.
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•A novel polycaprolactone (PCL)-based bilayer vascular graft was fabricated via electrospinning.•The thin inner layer of aligned PCL/collagen nanofibers enabled endothelial cell adherence and rapid migration.•The thick outer layer of randomly distributed PCL/silica nanofibers enhanced mechanical properties and fibroblasts affinity.
Solitary fibrous tumors (SFTs) are
NAB2
-
STAT6
fusion-associated neoplasms. There are several subtypes of
NAB2-STAT6
fusions, but their clinical significances are still unclear. Moreover, the ...mechanisms of malignant progression are also poorly understood. In this study, using 91 SFT cases, we examined whether fusion variants are associated with clinicopathological parameters and also investigated the molecular mechanism of malignant transformation using whole-exome sequencing. We detected variant 1b (
NAB2
ex4-
STAT6
ex2) in 51/91 (56%) cases and variants 2a/2b (
NAB2
ex6-
STAT6
ex16/17) in 17/91 (19%) cases. The
NAB2-STAT6
fusion variant types were significantly associated with their primary site (
P
< 0.001). In addition, a
TERT
promoter mutation was detected in 7/73 (10%) cases, and it showed a significant association with malignant SFTs (
P
= 0.003). To identify molecular changes during malignant progression, we selected an index patient to obtain parallel tissue samples from the primary and metastatic tumors. In the metastatic tissue, 10 unique molecular alterations, including those in
TP53
and
APAF1
, were detected. In vitro functional experiments showed that
APAF1
depletion increased the tumor potency of cells expressing NAB2-STAT6 fusion protein under treatment with staurosporine. We found that TP53 immunopositivity (
P
= 0.006) and loss of APAF1 immunoreactivity (
P
< 0.001) were significantly associated with malignant SFTs. Our study suggests that dysfunction of
TP53
and
APAF1
leads to impaired apoptotic function, and eventually contributes toward malignant SFT transformation.
Key messages
We firstly found that the
TERT
promoter mutation was strongly associated with malignant SFTs (
P
= 0.003) and the representative 1b (
NAB2
ex4-
STAT6
ex2) or 2a (
NAB2
ex6-
STAT6
ex16) fusion variants similarly contribute to tumorigenicity.
We also found that TP53 immunopositivity (
P
= 0.006) and loss of APAF1 immunoreactivity (
P
< 0.001) were significantly associated with malignant SFTs.
Our study suggests that dysfunction of
TP53
and
APAF1
leads to impaired apoptotic function, and eventually contributes toward malignant SFT transformation.
Delayed diagnosis of congenital tuberculosis (TB) in the neonatal intensive care unit (NICU) is a serious problem in terms of infection control. Here, we report our preemptive infection control ...activities implemented after the diagnosis of miliary TB in a mother of preterm twins (index twins, NB1 and NB2) in the NICU. In addition, we reviewed previous case reports of congenital TB exposure in the NICU setting. Immediately after diagnosing miliary TB in the mother, the index twins were isolated before their TB diagnosis and received preemptive anti-TB medication; contact investigations were also conducted. Eventually, NB1 was diagnosed with congenital TB at 29 days of age, and NB2 showed no definite evidence of TB. Through contact investigation, 11 of the 16 exposed infants received isoniazid prophylaxis and no positive tuberculin skin test results were obtained after 3 months. One of the 31 exposed healthcare workers showed new interferon-gamma release assay conversion. Moreover, our case showed a much shorter contagious period compared to that in previous reports (8 versus 17–102 days). This suggests that a high index of suspicion and prompt measures can help prevent congenital TB outbreaks and reduce the burden of infection control activities in the NICU.
In electronic warfare systems, detecting low-probability-of-intercept (LPI) radar signals poses a significant challenge due to the signal power being lower than the noise power. Techniques using ...statistical or deep learning models have been proposed for detecting low-power signals. However, as these methods overlook the inherent characteristics of radar signals, they possess limitations in radar signal detection performance. We introduce a deep learning-based detection model that capitalizes on the periodicity characteristic of radar signals. The periodic autocorrelation function (PACF) is an effective time-series data analysis method to capture the pulse repetition characteristic in the intercepted signal. Our detection model extracts radar signal features from PACF and then detects the signal using a neural network employing long short-term memory to effectively process time-series features. The simulation results show that our detection model outperforms existing deep learning-based models that use conventional autocorrelation function or spectrogram as an input. Furthermore, the robust feature extraction technique allows our proposed model to achieve high performance even with a shallow neural network architecture and provides a lighter model than existing models.
We present a centrifugal microfluidic device which enables multiplex foodborne pathogen identification by loop-mediated isothermal amplification (LAMP) and colorimetric detection using Eriochrome ...Black T (EBT). Five identical structures were designed in the centrifugal microfluidic system to perform the genetic analysis of 25 pathogen samples in a high-throughput manner. The sequential loading and aliquoting of the LAMP cocktail, the primer mixtures, and the DNA sample solutions were accomplished by the optimized zigzag-shaped microchannels and RPM control. We targeted three kinds of pathogenic bacteria (Escherichia coli O157:H7, Salmonella typhimurium and Vibrio parahaemolyticus) and detected the amplicons of the LAMP reaction by the EBT-mediated colorimetric method. For the limit-of-detection (LOD) test, we carried out the LAMP reaction on a chip with serially diluted DNA templates of E. coli O157:H7, and could observe the color change with 380 copies. The used primer sets in the LAMP reaction were specific only to the genomic DNA of E. coli O157:H7, enabling the on-chip selective, sensitive, and high-throughput pathogen identification with the naked eyes. The entire process was completed in 60min. Since the proposed microsystem does not require any bulky and expensive instrumentation for end-point detection, our microdevice would be adequate for point-of-care (POC) testing with high simplicity and high speed, providing an advanced genetic analysis microsystem for foodborne pathogen detection.
•A centrifugal LAMP microdevice for pathogen detection was developed.•Zigzag-shaped microchannels provide sequential aliquoting of the LAMP components.•Simple and user-friendly EBT-mediated colorimetric detection method was devised.•The proposed system does not require any bulky or expensive instrument for detection.•This microdevice would be adequate for point-of-care pathogen detection.
Background
We evaluated the therapeutic efficacy of GC1118, a novel anti‐epidermal growth factor receptor (EGFR) monoclonal antibody, in recurrent glioblastoma (GBM) patients with EGFR amplification.
...Methods
This study was a multicenter, open‐label, single‐arm phase II trial. Recurrent GBM patients with EGFR amplification were eligible: EGFR amplification was determined using fluorescence in situ hybridization analysis when a sample had both the EGFR/CEP7 ratio of ≥2 and a tight cluster EGFR signal in ≥10% of recorded cells. GC1118 was administered intravenously at a dose of 4 mg/kg once weekly. The primary endpoint was the 6‐month progression‐free survival rate (PFS6). Next‐generation sequencing was performed to investigate the molecular biomarkers related to the response to GC1118.
Results
Between April 2018 and December 2020, 21 patients were enrolled in the study and received GC1118 treatment. Eighteen patients were eligible for efficacy analysis. The PFS6 was 5.6% (95% confidence interval, 0.3%–25.8%, Wilson method). The median progression‐free survival was 1.7 months (range: 28 days–7.2 months) and median overall survival was 5.7 months (range: 2–22.0 months). GC1118 was well tolerated except skin toxicities. Skin rash was the most frequent adverse event and four patients experienced Grade 3 skin‐related toxicity. Genomic analysis revealed that the immune‐related signatures were upregulated in patients with tumor regression.
Conclusion
This study did not meet the primary endpoint (PFS6); however, we found that immune signatures were significantly upregulated in the tumors with regression upon GC1118 therapy, which signifies the potential of immune‐mediated antitumor efficacy of GC1118.
The choice of a group decision-making rule is one of the most important political issues. Buchanan and Tullock have provided a framework for analyzing the optimal k-majority rule from the perspective ...of "methodological individualism." They proposed the concept of "external costs" and "decision costs" and argued that the optimal k-majority rule takes place where the sum of these two costs-"total costs"-is minimized. Despite the fact that the approach is widely accepted as a tool for dealing with public decision-making rules, the study of formalizing these two costs in a quantitative manner has been relatively rare. We propose a systematic way of modeling these costs considering the assumptions mentioned by Buchanan and Tullock. We find that the resulting shape of the graphs is generally similar to that of the Buchanan-Tullock model, except for some minor details. Then, using this analytical model, we investigate several factors that could affect Buchanan-Tullock's two costs and the optimal k-majority rule. We show that "clustering of disadvantages" (social factor) and "loss aversion" (personal factor) could increase external costs in Buchanan-Tullock's model. These factors can result in a separation between the theoretical and actual optimal k-majority rules. Meanwhile, some recent developments in information and communication technologies can not only decrease decision costs, but also increase the same costs simultaneously through amplified "group polarization" (technological factor). If the effect of the former is not the same as that of the latter, this leads to a difference in optimal k-majority rules as well. These discrepancies bring us to the dilemma of "public choice before public choice."
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Water evaporation-driven energy harvesting is an emerging mechanism for contributing to green energy production with low cost. Herein, we developed polyacrylonitrile (PAN) nanofiber-based ...evaporation-driven electricity generators (PEEGs) to confirm the feasibility of utilizing electrospun PAN nanofiber mats in an evaporation-driven energy harvesting system. However, PAN nanofiber mats require a support substrate to enhance its durability and stability when it is applied to an evaporation-driven energy generator, which could have additional effects on generation performance. Accordingly, various support substrates, including fiberglass, copper, stainless mesh, and fabric screen, were applied to PEEGs and examined to understand their potential impacts on electrical generation outputs. As a result, the PAN nanofiber mats were successfully converted to a hydrophilic material for an evaporation-driven generator by dip-coating them in nanocarbon black (NCB) solution. Furthermore, specific electrokinetic performance trends were investigated and the peak electricity outputs of
were recorded to be 150.8, 6.5, 2.4, and 215.9 mV, and
outputs were recorded to be 143.8, 60.5, 103.8, and 121.4 μA, from PEEGs with fiberglass, copper, stainless mesh, and fabric screen substrates, respectively. Therefore, the implications of this study would provide further perspectives on the developing evaporation-induced electricity devices based on nanofiber materials.
Objectives
To develop a model for differentiating the predominant subtype-based prognostic groups of lung adenocarcinoma using CT radiomic features, and to validate its performance in comparison with ...radiologists’ assessments.
Methods
A total of 993 patients presenting with invasive lung adenocarcinoma between March 2010 and June 2016 were identified. Predominant histologic subtypes were categorized into three groups according to their prognosis (group 0: lepidic; group 1: acinar/papillary; group 2: solid/micropapillary). Seven hundred eighteen radiomic features were extracted from segmented lung cancers on contrast-enhanced CT. A model-development set was formed from the images of 893 patients, while 100 image sets were reserved for testing. A least absolute shrinkage and selection operator method was used for feature selection. Performance of the radiomic model was evaluated using receiver operating characteristic curve analysis, and accuracy on the test set was compared with that of three radiologists with varying experiences (6, 7, and 19 years in chest CT).
Results
Our model differentiated the three groups with areas under the curve (AUCs) of 0.892 and 0.895 on the development and test sets, respectively. In pairwise discrimination, the AUC was highest for group 0 vs. 2 (0.984). The accuracy of the model on the test set was higher than the averaged accuracy of the three radiologists without statistical significance (73.0% vs. 61.7%,
p
= 0.059). For group 2, the model achieved higher PPV than the observers (85.7% vs. 35.0–48.4%).
Conclusions
Predominant subtype-based prognostic groups of lung adenocarcinoma were classified by a CT-based radiomic model with comparable performance to radiologists.
Key Points
• A CT-based radiomic model differentiated three prognosis-based subtype groups of lung adenocarcinoma with areas under the curve (AUCs) of 0.892 and 0.895 on development and test sets, respectively.
• The CT-based radiomic model showed near perfect discrimination between group 0 and group 2 (AUCs, 0.984–1.000).
• The accuracy of the CT-based radiomic model was comparable to the averaged accuracy of the three radiologists with 6, 7, and 19 years of clinical experience in chest CT (73.0% vs. 61.7%, p = 0.059), achieving a higher positive predictive value for group 2 than the observers (85.7% vs. 35.0–48.4%).
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