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Severe pelvic hemorrhage significantly contributes to mortality in trauma patients, yet the most effective treatment for severe pelvic injuries remains unclear. This systematic review evaluates the mortality and morbidity associated with bilateral internal iliac artery ligation (BIIAL) in patients experiencing severe hemorrhage from traumatic pelvic fractures. Comprehensive searches were conducted in MEDLINE PubMed, EMBASE, and Cochrane databases until February 7, 2024, to identify relevant articles. The risk of bias in observational studies was assessed using the ROBINS-I tool, which evaluates bias risk in nonrandomized intervention studies. The primary outcome was mortality following BIIAL, with the secondary outcome being complications related to the procedure. The review included eight studies, all observational. The overall mortality rate after BIIAL ranged from 45.0% to 76.9%. Ischemic complications from BIIAL were infrequent. A high and unclear risk of bias due to confounding and participant selection was noted across the studies. Four studies highlighted distinct indications for BIIAL compared to angioembolization. BIIAL was employed for patients with severe hemodynamic instability or when angiography was not available. Due to geographical limitations and significant heterogeneity among the studies reviewed, the true effect size of BIIAL remains indeterminate. Nevertheless, further prospective studies with robust designs are necessary. BIIAL holds potential as a viable option when angioembolization is not accessible or in cases of critical patient instability.

Reliable multilevel inverter IGBT modules require precise loss and heat management, particularly in severe traction applications. This paper presents a comprehensive modeling framework for three-level T-type neutral-point clamped (TNPC) inverters using a high-power Insulated Gate Bipolar Transistor (IGBT) module that combines model predictive control (MPC) with space vector pulse width modulation (SVPWM). The particle swarm optimization (PSO) algorithm is used to methodically tune the MPC cost function weights for minimization, while achieving a balance between output current tracking, stabilization of the neutral-point voltage, and, consequently, a uniform distribution of thermal stress. The proposed SVPWM-MPC algorithm selects optimal switching states, which are then utilized in a chip-level loss model coupled with a Cauer RC thermal network to predict transient chip-level junction temperatures dynamically. The proposed framework is executed in MATLAB R2024b and validated with experiments, and the SemiSel industrial thermal simulation tool, demonstrating both control effectiveness and accuracy of the electro-thermal model. The results demonstrate that the proposed control method can sustain neutral-point voltage imbalance of less than 0.45% when operating at 25% load and approximately 1% under full load working conditions, while accomplishing a uniform junction temperature profile in all inverter legs across different working conditions. Moreover, the results indicate that the proposed control and modeling structure is an effective and common-sense way to perform coordinated electrical and thermal management, effectively allowing for predesign and reliability testing of high-power TNPC inverters.

Monitoring the peak junction hotspot temperature in IGBT modules is critical for ensuring the reliability of high-power industrial multilevel inverters, particularly when operating under extreme thermal conditions, such as in traction applications. This study presents a comprehensive chip-level analytical loss and thermal model for estimation of the peak junction hotspot temperature in a three-level T-type neutral-point-clamped (TNPC) IGBT module. The developed model includes a detailed analytical assessment of conduction and switching losses, along with transient thermal network modeling, based on the actual electrical and thermal characteristics of the IGBT module. Additionally, a hybrid thermal–electrical stress experimental setup, designed to replicate real operating conditions, was implemented for a balanced three-phase inverter circuit utilizing a Semikron three-level IGBT module, with testing currents reaching 100 A and a critical case temperature of 125 °C. The analytically estimated module losses and peak junction hotspot temperatures were validated through direct experimental measurements. Furthermore, thermal simulations were conducted with Semikron’s SemiSel benchmark tool to cross-validate the accuracy of the thermo-electrical model. The outcomes show a relative estimation error of less than 1% when compared to experimental data and approximately 1.15% for the analytical model. These findings confirm the model’s accuracy and enhance the reliability evaluation of TNPC-IGBT modules in extreme thermal environments.

This preliminary study aimed to screen non-coding RNAs (ncRNAs) from plasma exosomes as a new method for cervical cancer diagnosis. Differentially expressed RNAs were initially selected from among a group of 12 healthy individuals (normal group) and a pretreatment group of 30 patients with cervical cancer (cancer group). Then, we analyzed the association between an ncRNA-mRNA network and cancer using ingenuity pathway analysis after secondary selection according to the number and correlation of mRNAs (or ncRNAs) relative to changes in the expression of primarily selected ncRNAs (or mRNAs) before and after chemoradiotherapy. The number of RNAs selected from the initial RNAs was one from 13 miRNAs, four from 42 piRNAs, four from 28 lncRNAs, nine from 18 snoRNAs, 10 from 76 snRNAs, nine from 474 tRNAs, nine from 64 yRNAs, and five from 67 mRNAs. The combination of miRNA (miR-142-3p), mRNAs (CXCL5, KIF2A, RGS18, APL6IP5, and DAPP1), and snoRNAs (SNORD17, SCARNA12, SNORA6, SNORA12, SCRNA1, SNORD97, SNORD62, and SNORD38A) clearly distinguished the normal samples from the cancer group samples. We present a method for efficiently screening eight classes of RNAs isolated from exosomes for cervical cancer diagnosis using mRNAs (or ncRNAs) altered by chemoradiotherapy.

Gallium-based liquid metals (LMs) are promising materials for stretchable electronics due to their metallic conductivity and deformability. However, the fabrication of large-area stretchable integrated electronics using LMs on various polymers remains challenging due to their high surface tension, fluidity, and poor wettability. Current techniques, such as selective wetting and lift-off processes, face limitations related to substrate compatibility and Ga/metal alloying, hindering their applicability in integrated electronic systems. To address these challenges, we developed a high-resolution top-down etching-based photolithography combined with a universal cryogenic transfer method for transferring patterned LM particles (LMPs) in various polymer substrates. The cryogenic environment modifies the interfacial bonding between the LMPs and substrates, resulting in a universal transfer. The resulting liquid metal particle network embedded polymer (LNEP) exhibits high electrical conductivity (~1.71 × 10⁶ S/m), stability, and strain-insensitive performance across various polymers. This process is scalable to large-area fabrication, overcoming the limitations of existing LM patterning techniques. Leveraging this approach, we demonstrated the use of LNEP ranging from skin-conformal wearable sensors to hybrid stretchable circuits and implantable devices, demonstrating the universality of the method. This technique establishes a scalable pathway for stretchable electronics in advanced applications. Stretchable liquid-metal electronics is limited by high surface tension, fluidity, and poor wettability. Here, Lee et. al. presents a universal cryogenic transfer method for liquid metal particles, enabling high-throughput fabrication of wafer-scale stretchable integrated electronics with robust electrical performance.

Osteoporosis is a disease caused by impaired bone remodeling that is especially prevalent in elderly and postmenopausal women. Although numerous chemical agents have been developed to prevent osteoporosis, arguments remain regarding their side effects. Here, we demonstrated the effects of loganin, a single bioactive compound isolated from Cornus officinalis, on osteoblast and osteoclast differentiation in vitro and on ovariectomy (OVX)-induced osteoporosis in mice in vivo. Loganin treatment increased the differentiation of mouse preosteoblast cells into osteoblasts and suppressed osteoclast differentiation in primary monocytes by regulating the mRNA expression levels of differentiation markers. Similar results were obtained in an osteoblast–osteoclast co-culture system, which showed that loganin enhanced alkaline phosphatase (ALP) activity and reduced TRAP activity. In in vivo experiments, the oral administration of loganin prevented the OVX-induced loss of bone mineral density (BMD) and microstructure in mice and improved bone parameters. In addition, loganin significantly increased the serum OPG/RANKL ratio and promoted osteogenic activity during bone remodeling. Our findings suggest that loganin could be used as an alternative treatment to protect against osteoporosis.

This systematic review and meta-analysis aimed to investigate the ultrasonographic variation of the diameter of the inferior vena cava (IVC), internal jugular vein (IJV), subclavian vein (SCV), and femoral vein (FV) to predict fluid responsiveness in critically ill patients. Relevant articles were obtained by searching PubMed, EMBASE, and Cochrane databases (articles up to 21 October 2021). The number of true positives, false positives, false negatives, and true negatives for the index test to predict fluid responsiveness was collected. We used a hierarchical summary receiver operating characteristics model and bivariate model for meta-analysis. Finally, 30 studies comprising 1719 patients were included in this review. The ultrasonographic variation of the IVC showed a pooled sensitivity and specificity of 0.75 and 0.83, respectively. The area under the receiver operating characteristics curve was 0.86. In the subgroup analysis, there was no difference between patients on mechanical ventilation and those breathing spontaneously. In terms of the IJV, SCV, and FV, meta-analysis was not conducted due to the limited number of studies. The ultrasonographic measurement of the variation in diameter of the IVC has a favorable diagnostic accuracy for predicting fluid responsiveness in critically ill patients. However, there was insufficient evidence in terms of the IJV, SCV, and FV.

The aim of the study is to develop artificial intelligence (AI) algorithm based on a deep learning model to predict mortality using abbreviate injury score (AIS). The performance of the conventional anatomic injury severity score (ISS) system in predicting in-hospital mortality is still limited. AIS data of 42,933 patients registered in the Korean trauma data bank from four Korean regional trauma centers were enrolled. After excluding patients who were younger than 19 years old and those who died within six hours from arrival, we included 37,762 patients, of which 36,493 (96.6%) survived and 1269 (3.4%) deceased. To enhance the AI model performance, we reduced the AIS codes to 46 input values by organizing them according to the organ location (Region-46). The total AIS and six categories of the anatomic region in the ISS system (Region-6) were used to compare the input features. The AI models were compared with the conventional ISS and new ISS (NISS) systems. We evaluated the performance pertaining to the 12 combinations of the features and models. The highest accuracy (85.05%) corresponded to Region-46 with DNN, followed by that of Region-6 with DNN (83.62%), AIS with DNN (81.27%), ISS-16 (80.50%), NISS-16 (79.18%), NISS-25 (77.09%), and ISS-25 (70.82%). The highest AUROC (0.9084) corresponded to Region-46 with DNN, followed by that of Region-6 with DNN (0.9013), AIS with DNN (0.8819), ISS (0.8709), and NISS (0.8681). The proposed deep learning scheme with feature combination exhibited high accuracy metrics such as the balanced accuracy and AUROC than the conventional ISS and NISS systems. We expect that our trial would be a cornerstone of more complex combination model.

Kaempferol, a bioflavonoid present in fruits and vegetables, has a variety of antioxidant and anti-inflammatory capacities, but the functional role of kaempferol in oxidative skin dermal damage has yet to be well studied. In this study, we examine the role of kaempferol during the inflammation and cell death caused by 12-O-tetradecanoylphorbol-13-acetate (TPA) in normal human dermal fibroblasts (NHDF). TPA (5 μM) significantly induced cytotoxicity of NHDF, where a robust increase in the interleukin (IL)-1β mRNA among the various pro-inflammatory cytokines. The skin fibroblastic cytotoxicity and IL-1β expression induced by TPA were significantly ameliorated by a treatment with 100 nM of kaempferol. Kaempferol blocked the production of the intracellular reactive oxygen species (ROS) responsible for the phosphorylation of c-Jun N-terminal kinase (JNK) induced by TPA. Interestingly, we found that kaempferol inhibited the phosphorylation of nuclear factor-kappa B (NF-κB) and the inhibitor NF-κB (IκBα), which are necessary for the expression of cleaved caspase-3 and the IL-1β secretion in TPA-treated NHDF. These results suggest that kaempferol is a functional agent that blocks the signaling cascade of the skin fibroblastic inflammatory response and cytotoxicity triggered by TPA.

Plasma exosomal miRNAs are key regulators of cell-cell interactions associated with several biological functions in patients with cancer. This pilot study aimed to investigate the log2 fold change (log2FC) of the expression of exosomal miRNAs and related mRNAs in the blood of patients with cervical cancer to identify prognostic markers better than those currently available. We sequenced plasma exosomal RNA from 56 blood samples collected from 28 patients with cervical cancer, who had been treated with concurrent chemoradiotherapy (CCRT). Changes in the expression of miRNAs and mRNAs before and after CCRT were represented as log2FC. Their biological functions were studied by miRNA-mRNA network analysis, using ingenuity pathway analysis, after the selection of two groups of miRNAs, each associated with early progression (EP) and metastasis, also described as initial stage. Seven patients experienced EP, three of whom died within four months after progression. Reduced levels of miR-1228-5p, miR-33a-5p, miR-3200-3p, and miR-6815-5p and increased levels of miR-146a-3p in patients with EP revealed unresolved inflammation, with accompanying increased expression of PCK1 and decreased expression of FCGR1A. Increased levels of miR-605-5p, miR-6791-5p, miR-6780a-5p, and miR-6826-5p and decreased levels of miR-16-1-3p (or 15a-3p) were associated with the degree of metastasis and led to the systemic activation of myeloid, endothelial, and epithelial cells, as well as neurons, phagocytes, and platelets. Log2FCs in the expression of miRNAs and mRNAs from plasma exosomes after CCRT are associated with EP and metastasis, reflecting unresolved inflammation and systemic microenvironmental factors, respectively. However, this study, supported by preliminary data insufficient to reach clear conclusions, should be verified in larger prospective cohorts.