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The cytoskeleton, a dynamic network of structural proteins within cells, is essential for cellular deformation and responds to external mechanical cues. Here, based on the structure of the cytoskeleton, combined with the biochemical reactions of the activator RhoA and the inhibitor F-actin, we develop a novel mechanochemical cytoskeleton model to investigate the mechanical behavior of cells. Interestingly, we find that active stress fibers exhibit diverse dynamical modes at specific inhibitor concentration thresholds. The existence of concentration differences and sustained mechanochemical feedback in activators and inhibitors trigger a global oscillation of isolated cells. In addition, under uniaxial and biaxial stretches, activators and inhibitors preferentially diffuse toward the more significantly deformed cytoskeletal elements, and their dynamic interactions regulate the cell to align with the main stretching direction. Our findings, consistent with many experimental results, provide fundamental insights into cytoskeletal remodeling and cellular mechanosensing mechanisms. [ABSTRACT FROM AUTHOR]

IntroductionPneumonia is a common infection in the intensive care unit (ICU), and gram-negative bacilli are the most common bacterial cause. The purpose of the study was to investigate the risk factors for 30-day mortality in patients with gram-negative bacillary pneumonia in the ICU, construct a predictive model, and stratify patients based on risk to assess their short-term survival.MethodsPatients admitted to the ICU with gram-negative bacillary pneumonia at Fujian Medical University Affiliated First Hospital between January 2018 and September 2020 were selected. Patients were divided into deceased and survivor groups based on whether death occurred within 30 days. Multifactorial logistic regression analysis was used to identify independent risk factors for 30-day mortality in these patients, and a predictive nomogram model was constructed based on these factors. Patients were categorized into low-, medium-, and high-risk groups according to the model's predicted probability, and Kaplan-Meier survival curves were plotted to assess short-term survival.ResultsThe study included 305 patients. Lactic acid (odds ratio [OR], 1.524, 95% CI: 1.057-2.197), tracheal intubation (OR: 4.202, 95% CI: 1.092-16.169), and acute kidney injury (OR:4.776, 95% CI: 1.632-13.978) were identified as independent risk factors for 30-day mortality. A nomogram prediction model was established based on these three factors. Internal validation of the model showed a Hosmer-Lemeshow test result of X2=5.770, P=0.834, and an area under the ROC curve of 0.791 (95% CI: 0.688-0.893). Bootstrap resampling of the original data 1000 times yielded a C-index of 0.791, and a decision curve analysis indicated a high net benefit when the threshold probability was between 15%-90%. The survival time for low-, medium-, and high-risk patients was 30 (30, 30), 30 (16.5, 30), and 17 (11, 27) days, respectively, which were significantly different.ConclusionLactic acid, tracheal intubation, and acute kidney injury were independent risk factors for 30-day mortality in patients in the ICU with gram-negative bacillary pneumonia. The predictive model constructed based on these factors showed good predictive performance and helped assess short-term survival, facilitating early intervention and treatment.

The bone marrow (BM) niches are the complex microenvironments that surround cells, providing various external stimuli to regulate a range of haematopoietic stem cell (HSC) behaviours. Recently, it has been proposed that the fate decision of HSCs is often correlated with significantly altered biophysical signals of BM niches. To thoroughly elucidate the effect of mechanical microenvironments on cell fates, we constructed 2D and 3D cell culture hydrogels using polyacrylamide to replicate the mechanical properties of heterogeneous sub‐niches, including the inherent rigidity of marrow adipose tissue (2 kPa), perivascular tissue (8 kPa) and endosteum region (35 kPa) in BM. Our observations suggest that HSCs can respond to the mechanical heterogeneity of the BM microenvironment, exhibiting diversity in cell mechanics, haematopoietic pool maintenance and differentiated lineages. Hydrogels with higher stiffness promote the preservation of long‐term repopulating HSCs (LT‐HSCs), while those with lower stiffness support multi‐potent progenitors (MPPs) viability in vitro. Furthermore, we established a comprehensive transcriptional profile of haematopoietic subpopulations to reflect the multipotency of haematopoietic stem and progenitor cells (HSPCs) that are modulated by niche‐like stiffness. Our findings demonstrate that HSPCs exhibit completely distinct downstream differentiated preferences within hydrogel systems of varying stiffness. This highlights the crucial role of tissue‐specific mechanical properties in HSC lineage decisions, which may provide innovative solutions to clinical challenges. [ABSTRACT FROM AUTHOR]

The corrosion resistance of titanium alloy poses a crucial challenge, significantly affecting its prospect for service and application. The present study aimed to investigate the corrosion resistance of Ti-6Al-4V ELI alloys with varying surface roughness in hydrofluoric acid solution, in order to assess the influence of roughness on their corrosion resistance performance. The weight loss percentage, surface morphology evolution, and roughness variation of Ti-6Al-4V ELI alloys before and after exposure to hydrofluoric acid corrosion were characterized. While the weight loss and weight loss percentage of the Ti-6Al-4V ELI alloy increased with prolonged corrosion, the overall weight loss rate decreased. The accumulation of TiF3 phases and depletion of the Ti-6Al-4V ELI matrix mutually led to the alterations of the surface roughness. Due to the inability to prevent fluoride ions from contacting with the Ti-6Al-4V ELI alloy, continuous corrosion occurred in hydrofluoric acid. Based on these experimental results and analysis, the corrosion mechanism of the Ti-6Al-4V ELI alloy corroded by hydrofluoric acid solution was elucidated. Furthermore, an analysis was conducted to explore the influence of corrosion time on mechanical properties by analyzing the decay in compressive properties of the Ti-6Al-4V ELI titanium alloy after hydrofluoric acid corrosion treatment. The bearing capacity of the Ti-6Al-4V ELI alloy deteriorated over the corrosion time. [ABSTRACT FROM AUTHOR]

Sows suffer oxidative stress and inflammation induced by metabolic burden during late pregnancy, which negatively regulates reproductive and lactating performances. We previously found that L-malic acid (MA) alleviated oxidative stress and inflammation and improved reproductive performances in sows. However, the mechanism underlying the MA's positive effects remains unexplored. Here, twenty Large White × Landrace sows with similar parity were randomly divided into two groups and fed with a basal diet or a diet supplemented with 2% L-malic acid complex from day 85 of gestation to delivery. The gut microbiome, fecal short-chain fatty acids, and untargeted serum metabolome were determined. Results showed that Firmicutes, Bacteroidota, and Spirochaetota were the top abundant phyla identified in late pregnancy for sows. Maternal MA supplementation modulated the composition but not the richness and diversity of gut microbiota during late pregnancy. Correlation analysis between gut microbiota and antioxidant capacity (or inflammation indicators) revealed that unclassified_f_Ruminococcaceae, unclassified_f_Lachnospiraceae, UCG-002, norank_f_norank_o_RF3, and Lactobacillus might play a role in anti-oxidation, and Lachnospiraceae_XPB1014_group, Lachnospiraceae_NK4A136_group, UCG-002, unclassified_f_Ruminococcaceae, Candidatus_Soleaferrea, norank_f_UCG-010, norank_f_norank_o_RF39, and unclassified_f_Lachnospiraceae might be involved in the anti-inflammatory effect. The improved antioxidant and inflammation status induced by MA might be independent of short chain fatty acid changes. In addition, untargeted metabolomics analysis exhibited different metabolic landscapes of sows in the MA group from in the control group and revealed the contribution of modified amino acid and lipid metabolism to the improved antioxidant capacity and inflammation status. Notably, correlation results of gut microbiota and serum metabolites, as well as serum metabolites and antioxidant capacity (or inflammation indicators), demonstrated that differential metabolism was highly related to the fecal microorganisms and antioxidant or inflammation indicators. Collectively, these data demonstrated that a maternal dietary supply of MA can ameliorate oxidative stress and inflammation in sows through modulating gut microbiota and host metabolic profiles during late pregnancy. [ABSTRACT FROM AUTHOR]

Biometric sensing has become a widely concerned authentication technology. Existing image-based methods are susceptible to light conditions and have privacy exposure risks, while contact authentication methods are not conducive to epidemic prevention requirements in public places. In this article, we propose a palmprint-based identification system by collecting backscattered signals of the inaudible acoustic signals, namely AcoPalm. AcoPalm does not require special hardware and contact operation for user authentication. First, frequency modulated continuous wave (FMCW) on acoustic signals are designed to extract static contours and palmprint changes and to model the unique biological characteristics of the individual palm. Second, a palmprint authentication model based on PENN is proposed to achieve high-precision multiuser authentication without mass training data. Finally, the system performance is evaluated in multiple smartphones and three scenarios. The experimental results show that AcoPalm can resist replay attack and imitation attack, and the authentication accuracy can reach 96.22%. Furthermore, AcoPalm achieves satisfactory experience in availability and practicality. [ABSTRACT FROM AUTHOR]

With the development of ubiquitous mobile devices, biometrics authentication has received much attention from researchers. For immersive experiences in AR (augmented reality), convenient continuous biometric authentication technologies are required to provide security for electronic assets and transactions through head-mounted devices. Existing fingerprint or face authentication methods are vulnerable to spoof attacks and replay attacks. In this paper, we propose MetaEar, which harnesses head-mounted devices to send FMCW (Frequency-Modulated Continuous Wave) ultrasonic signals for continuous biometric authentication of the human ear. CIR (channel impulse response) leveraged the channel estimation theory to model the physiological structure of the human ear, called the Ear Related Transfer Function (ERTF). It extracts unique representations of the human ear's intrinsic and extrinsic biometric features. To overcome the data dependency of Deep Learning and improve its deployability in mobile devices, we use the lightweight learning approach for classification and authentication. Our implementation and evaluation show that the average accuracy can reach about 96% in different scenarios with small amounts of data. MetaEar enables one to handle immersive deployable authentication and be more sensitive to replay and impersonation attacks. [ABSTRACT FROM AUTHOR]

Infertility is a global reproductive disorder which is caused by a variety of complex diseases. Infertility affects the individual, family, and community through physical, psychological, social and economic consequences. The results from recent preclinical studies regarding stem cell-based therapies are promising. Stem cell-based therapies cast a new hope for infertility treatment as a replacement or regeneration strategy. The main features and application prospects of mesenchymal stem cells in the future of infertility should be understood by clinicians. Mesenchymal stem cells (MSCs) are multipotent stem cells with abundant source, active proliferation, and multidirectional differentiation potential. MSCs play a role through cell homing, secretion of active factors, and participation in immune regulation. Another advantage is that, compared with embryonic stem cells, there are fewer ethical factors involved in the application of MSCs. However, a number of questions remain to be answered prior to safe and effective clinical application. In this review, we summarized the recent status of MSCs in the application of the diseases related to or may cause to infertility and suggest a possible direction for future cytotherapy to infertility. [ABSTRACT FROM AUTHOR]

Growth differentiation factor 5 (GDF5) was reported to regulate brown adipogenesis; however, its effects on insulin sensitivity, full metabolic syndrome spectrum, and the thermogenesis in subcutaneous white adipose tissue (sWAT) have not been elucidated yet. We thus generated fatty acid-binding protein 4 (Fabp4)-GDF5 transgenic (TG) mice and showed that GDF5 TG mice developed a relative lean phenotype on a high-fat diet (HFD) and showed increased insulin sensitivity. Over expression of GDF5 in adipose tissues greatly promoted the thermogenic process in sWAT after cold or β3-agonist treatment. In TG mice, sWAT showed an important thermogenic effect as the thermogenic gene expression was markedly increased, which was consistent with the typical features of beige adipocytes. Moreover, knockdown of the protein GDF5 impaired browning program in sWAT after thermogenic stimuli. Enhanced mitogen-activated protein kinase (MAPK)/activating transcription factor 2 (ATF2) signaling was also identified in sWAT of HFD-fed GDF5 mice, and thermogenesis in mature adipocytes induced by GDF5 protein could be partly blocked by a p38 MAPK inhibitor. Taken together, our data suggest that GDF5 could improve insulin sensitivity and prevent metabolic syndrome, the adaptive thermogenesis in sWAT could mediate the obesity resistance effects of GDF5 in mice and partially resulted in the activation of the p38 MAPK signaling pathway. [ABSTRACT FROM AUTHOR]

Using the atomic force microscopy- (AFM-) PeakForce quantitative nanomechanical mapping (QNM) technique, we have previously shown that the adventitia of the human internal mammary artery (IMA), tested under dehydrated conditions, is altered in patients with a high degree of arterial stiffening. In this study, we explored the nanoscale elastic modulus of the tunica media of the IMA in hydrated and dehydrated conditions from the patients with low and high arterial stiffening, as assessed in vivo by carotid-femoral pulse wave velocity (PWV). In both hydrated and dehydrated conditions, the medial layer was significantly stiffer in the high PWV group. The elastic modulus of the hydrated and dehydrated tunica media was significantly correlated with PWV. In the hydrated condition, the expression activity of certain small leucine-rich repeat proteoglycans (SLRPs), which are associated with arterial stiffening, were found to be negatively correlated to the medial elastic modulus. We also compared the data with our previous work on the IMA adventitia. We found that the hydrated media and dehydrated adventitia are both suitable for reflecting the development of arterial stiffening and SLRP expression. This comprehensive study of the nanomechanical properties integrated with the proteomic analysis in the IMAs demonstrates the possibility of linking structural properties and function in small biological samples with novel AFM methods. The IMA is a suitable target for predicting arterial stiffening. [ABSTRACT FROM AUTHOR]

The collagen-rich adventitia is the outermost arterial layer and plays an important biomechanical and physiological role in normal vessel function. While there has been a lot of effort to understand the role of the medial layer on arterial biomechanics, the adventitia has received less attention. In this study, we hypothesized that different ultrastructural and nanomechanical properties would be exhibited in the adventitia of the internal mammary artery (IMA) in patients with a low degree of arterial stiffening as compared to those with a high degree of arterial stiffening. Human IMA biopsies were obtained from a cohort of patients with arterial stiffening assessed via carotid-femoral PWV. Patients were grouped as low PWV (8.5 ± 0.7 ms −1 , n = 8) and high PWV (13.4 ± 3.0 ms −1 , n = 9). Peakforce QNM atomic force microscopy (AFM) was used to determine the nanomechanical and morphological properties of the IMA. The nano-scale elastic modulus was found to correlate with PWV. We show for the first time that nano-scale alterations in adventitial collagen fibrils in the IMA are evident in patients with high PWV, even though the IMA is not involved in the carotid-femoral pathway. Our approach provides new insight into systemic structure-property changes in the vasculature, and also provides a method of characterizing small biopsy samples to predict the development of arterial stiffening. Statement of Significance Arterial stiffening occurs as part of the natural aging process and is strongly linked to cardiovascular risk. Although arterial stiffening is routinely measured in vivo , little is known about how localised changes in artery structure and biomechanics contributes to in vivo arterial stiffening. This study focusses on the role of the outermost layer of arteries, the adventitia, in arterial stiffening. The study provides data on nano-scale changes in collagen fibril structure and mechanical properties in the adventitia and shows how it relates to in vivo stiffness measurements in the vascular system. This is the first study to link in vivo arterial stiffening with nanomechanical changes in artery biopsy samples. Hence, this approach could be used to develop new diagnostic methods for vascular disease. [ABSTRACT FROM AUTHOR]

The underlying pathogenic lesions of glycogen storage disease type II (GSD II) and the diversity of this disease among different species are still under exploration. Thus, we created an acid alpha-glucosidase ( gaa) gene-mutated zebrafish model of GSD II and examined the sequential pathogenic changes. gaa mRNA and protein expression, enzymatic activity, and lysosomal glycogen accumulation were assessed, and the phenotypic changes were compared between wild-type (WT) and gaa-mutated zebrafish. The presence of a Δ13 frameshift mutation in the gaa gene was confirmed at both the DNA and transcribed mRNA levels by Sanger sequencing. The relative amount of gaa mRNA was decreased before 2 days postfertilization (dpf), after which it unexpectedly increased in the mutant compared with the WT zebrafish. Consistent with the mRNA expression, the Gaa enzymatic activity in the mutant was downregulated before 3 dpf, while the Gaa protein level was slightly decreased at 4 dpf and was maintained at a consistent level in the adult gaa mutant muscle tissue. However, more than half of the adult mutant zebrafish exhibited excessive glycogen accumulation in the liver and muscles, along with the presence of autophagosomes, as determined by transmission electron microscopy. Thus, we have successfully generated a frameshift mutation in the gaa gene in zebrafish. The unique gaa gene expression changes and mild GSD II features during the adult stage strongly indicate the existence of species-specific differences, as well as an underlying compensatory network, which may warrant further examination. [ABSTRACT FROM AUTHOR]

We present a new bend sensor which can measure the curvature using an etched fiber Bragg grating (FBG) embedded into a beam. The reflection power of the grating detected by an optical power meter varies linearly with the curvature of the beam. This sensor is independent of temperature. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 43: 414–417, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20486 [ABSTRACT FROM AUTHOR]

Studies of cell and tissue mechanics have shown that significant changes in cell and tissue mechanics during lesions and cancers are observed, which provides new mechanical markers for disease diagnosis based on machine learning. However, due to the lack of effective mechanic markers, only elastic modulus and iconographic features are currently used as markers, which greatly limits the application of cell and tissue mechanics in disease diagnosis. Here, we develop a liver pathological state classifier through a support vector machine method, based on high dimensional viscoelastic mechanical data. Accurate diagnosis and grading of hepatic fibrosis facilitates early detection and treatment and may provide an assessment tool for drug development. To this end, we used the viscoelastic parameters obtained from the analysis of creep responses of liver tissues by a self-similar hierarchical model and built a liver state classifier based on machine learning. Using this classifier, we implemented a fast classification of healthy, diseased, and mesenchymal stem cells (MSCs)-treated fibrotic live tissues, and our results showed that the classification accuracy of healthy and diseased livers can reach 0.99, and the classification accuracy of the three liver tissues mixed also reached 0.82. Finally, we provide screening methods for markers in the context of massive data as well as high-dimensional viscoelastic variables based on feature ablation for drug development and accurate grading of liver fibrosis. We propose a novel classifier that uses the dynamical mechanical variables as input markers, which can identify healthy, diseased, and post-treatment liver tissues., Competing Interests: J-TH, ZC, and G-KX were employed by the SVL. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhang, Hang, Chang, Yu, Yang and Xu.)

Accurate diagnosis and treatment assessment of liver fibrosis face significant challenges, including inherent limitations in current techniques like sampling errors and inter-observer variability. Addressing this, our study introduces a novel machine learning (ML) framework, which integrates light gradient boosting machine and multivariate imputation by chained equations to enhance liver status assessment using biomechanical markers. Building upon our previously established multiscale mechanical characteristics in fibrotic and treated livers, this framework employs Gaussian Bayesian optimization for post-imputation, significantly improving classification performance. Our findings indicate a marked increase in the precision of liver fibrosis diagnosis and provide a novel, quantitative approach for assessing fibrosis treatment. This innovative combination of multiscale biomechanical markers with advanced ML algorithms represents a transformative step in liver disease diagnostics and treatment evaluation, with potential implications for other areas in medical diagnostics., (© 2024 Institute of Physics and Engineering in Medicine.)

Background: Machine learning is a potentially effective method for predicting the response to platinum-based treatment for ovarian cancer. However, the predictive performance of various machine learning methods and variables is still a matter of controversy and debate., Objective: This study aims to systematically review relevant literature on the predictive value of machine learning for platinum-based chemotherapy responses in patients with ovarian cancer., Methods: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we systematically searched the PubMed, Embase, Web of Science, and Cochrane databases for relevant studies on predictive models for platinum-based therapies for the treatment of ovarian cancer published before April 26, 2023. The Prediction Model Risk of Bias Assessment tool was used to evaluate the risk of bias in the included articles. Concordance index (C-index), sensitivity, and specificity were used to evaluate the performance of the prediction models to investigate the predictive value of machine learning for platinum chemotherapy responses in patients with ovarian cancer., Results: A total of 1749 articles were examined, and 19 of them involving 39 models were eligible for this study. The most commonly used modeling methods were logistic regression (16/39, 41%), Extreme Gradient Boosting (4/39, 10%), and support vector machine (4/39, 10%). The training cohort reported C-index in 39 predictive models, with a pooled value of 0.806; the validation cohort reported C-index in 12 predictive models, with a pooled value of 0.831. Support vector machine performed well in both the training and validation cohorts, with a C-index of 0.942 and 0.879, respectively. The pooled sensitivity was 0.890, and the pooled specificity was 0.790 in the training cohort., Conclusions: Machine learning can effectively predict how patients with ovarian cancer respond to platinum-based chemotherapy and may provide a reference for the development or updating of subsequent scoring systems., (©Qingyi Wang, Zhuo Chang, Xiaofang Liu, Yunrui Wang, Chuwen Feng, Yunlu Ping, Xiaoling Feng. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 22.01.2024.)

Coicis Semen is an important food product and traditional Chinese medicine (TCM) derived from the dried and mature seeds of Coix lacryma-jobi L. var. ma-yuen (Roman.) Stapf. An increasing number of studies have investigated its use, either alone or in combination with other botanical drugs, to treat female reproductive system malignancies, and its pharmacological effects have been confirmed clinically. This review aims to provide an overview of Coicis Semen 's historical role in treating female reproductive system malignancies based on TCM theory, to summarize clinical trials results, and to analyze information pertaining to the main phytochemical components, pharmacokinetics, related anti-cancer pharmacological effects, and toxicology of Coicis Semen . Information on Coicis Semen was collected from internationally accepted scientific databases. Seventy-four clinical trials were identified that used Coicis Semen in combination with other Chinese medicine to treat female reproductive system malignancies, most of which demonstrated good anti-tumor efficacy and few adverse reactions. To date, more than 80 individual compounds have been isolated from this botanical drug. In terms of anti-tumor effects, Coix seed oil has been studied the most. Pharmacokinetic data suggest that the active ingredients in Coicis Semen are widely distributed after administration, and Coicis Semen and its active compounds play a beneficial role in treating female reproductive system malignancies. Mechanistically, the anti-cancer effects may be related to inhibition of tumor cell proliferation and promotion of apoptosis, inhibition of tumor angiogenesis, suppression of the chronic inflammatory microenvironment of tumors, modulation of immune function, and regulation of the female reproductive system. Most acute toxicity and genotoxicity studies have shown that Coicis Semen is non-toxic. However, the existing studies have many limitations, and the future research direction should emphasize 1) the relationship between drug concentration and pharmacological action as well as toxicity; 2) the structural modification or the synthesis of analogues led by the active ingredients of Coicis Semen to enhance pharmacological activities and bioavailability; 3) accurately revealing the anti-cancer pharmacological effects of Coicis Semen and its compounds through multi-omics technology. We hope that this review can determine future directions and inform novel drug development for treating female reproductive malignancies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Pan, Shen, Zhang, Zhang, Li, Chang and Pang.)