The transcription factor MYB156 controls the polar stiffening of guard cell walls in poplar.

The mechanical properties of guard cells have major effects on stomatal functioning. Reinforced stiffness in the stomatal polar regions was recently proposed to play an important role in stomatal function, but the underlying molecular mechanisms remain elusive. Here, we used genetic and biochemical approaches in poplar (Populus spp.) to show that the transcription factor MYB156 controls pectic homogalacturonan-based polar stiffening through the downregulation of the gene encoding pectin methylesterase 6 (PME6). Loss of MYB156 increased the polar stiffness of stomata, thereby enhancing stomatal dynamics and response speed to various stimuli. In contrast, overexpression of MYB156 resulted in decreased polar stiffness and impaired stomatal dynamics, accompanied by smaller leaves. Polar stiffening functions in guard cell dynamics in response to changing environmental conditions by maintaining normal stomatal morphology during stomatal movement. Our study revealed the structure-function relationship of the cell wall of guard cells in stomatal dynamics, providing an important means for improving the stomatal performance and drought tolerance of plants.

Soft Fiber Electronics Based on Semiconducting Polymer.

Fibers, originating from nature and mastered by human, have woven their way throughout the entire history of human civilization. Recent developments in semiconducting polymer materials have further endowed fibers and textiles with various electronic functions, which are attractive in applications such as information interfacing, personalized medicine, and clean energy. Owing to their ability to be easily integrated into daily life, soft fiber electronics based on semiconducting polymers have gained popularity recently for wearable and implantable applications. Herein, we present a review of the previous and current progress in semiconducting polymer-based fiber electronics, particularly focusing on smart-wearable and implantable areas. First, we provide a brief overview of semiconducting polymers from the viewpoint of materials based on the basic concepts and functionality requirements of different devices. Then we analyze the existing applications and associated devices such as information interfaces, healthcare and medicine, and energy conversion and storage. The working principle and performance of semiconducting polymer-based fiber devices are summarized. Furthermore, we focus on the fabrication techniques of fiber devices. Based on the continuous fabrication of one-dimensional fiber and yarn, we introduce two- and three-dimensional fabric fabricating methods. Finally, we review challenges and relevant perspectives and potential solutions to address the related problems.

Magnetosome-inspired synthesis of soft ferrimagnetic nanoparticles for magnetic tumor targeting.

Magnetic targeting is one of the most promising approaches for improving the targeting efficiency by which magnetic drug carriers are directed using external magnetic fields to reach their targets. As a natural magnetic nanoparticle (MNP) of biological origin, the magnetosome is a special "organelle" formed by biomineralization in magnetotactic bacteria (MTB) and is essential for MTB magnetic navigation to respond to geomagnetic fields. The magnetic targeting of magnetosomes, however, can be hindered by the aggregation and precipitation of magnetosomes in water and biological fluid environments due to the strong magnetic attraction between particles. In this study, we constructed a magnetosome-like nanoreactor by introducing MTB Mms6 protein into a reverse micelle system. MNPs synthesized by thermal decomposition exhibit the same crystal morphology and magnetism (high saturation magnetization and low coercivity) as natural magnetosomes but have a smaller particle size. The DSPE-mPEG-coated magnetosome-like MNPs exhibit good monodispersion, penetrating the lesion area of a tumor mouse model to achieve magnetic enrichment by an order of magnitude more than in the control groups, demonstrating great prospects for biomedical magnetic targeting applications.

Electrochemically-driven actuators: from materials to mechanisms and from performance to applications.

Soft actuators, pivotal for converting external energy into mechanical motion, have become increasingly vital in a wide range of applications, from the subtle engineering of soft robotics to the demanding environments of aerospace exploration. Among these, electrochemically-driven actuators (EC actuators), are particularly distinguished by their operation through ion diffusion or intercalation-induced volume changes. These actuators feature notable advantages, including precise deformation control under electrical stimuli, freedom from Carnot efficiency limitations, and the ability to maintain their actuated state with minimal energy use, akin to the latching state in skeletal muscles. This review extensively examines EC actuators, emphasizing their classification based on diverse material types, driving mechanisms, actuator configurations, and potential applications. It aims to illuminate the complicated driving mechanisms of different categories, uncover their underlying connections, and reveal the interdependencies among materials, mechanisms, and performances. We conduct an in-depth analysis of both conventional and emerging EC actuator materials, casting a forward-looking lens on their trajectories and pinpointing areas ready for innovation and performance enhancement strategies. We also navigate through the challenges and opportunities within the field, including optimizing current materials, exploring new materials, and scaling up production processes. Overall, this review aims to provide a scientifically robust narrative that captures the current state of EC actuators and sets a trajectory for future innovation in this rapidly advancing field.

CT radiomics-based model for predicting TMB and immunotherapy response in non-small cell lung cancer.

BACKGROUND: Tumor mutational burden (TMB) is one of the most significant predictive biomarkers of immunotherapy efficacy in non-small cell lung cancer (NSCLC). Radiomics allows high-throughput extraction and analysis of advanced and quantitative medical imaging features. This study develops and validates a radiomic model for predicting TMB level and the response to immunotherapy based on CT features in NSCLC. METHOD: Pre-operative chest CT images of 127 patients with NSCLC were retrospectively studied. The 3D-Slicer software was used to outline the region of interest and extract features from the CT images. Radiomics prediction model was constructed by LASSO and multiple logistic regression in a training dataset. The model was validated by receiver operating characteristic (ROC) curves and calibration curves using external datasets. Decision curve analysis was used to assess the value of the model for clinical application. RESULTS: A total of 1037 radiomic features were extracted from the CT images of NSCLC patients from TCGA. LASSO regression selected three radiomics features (Flatness, Autocorrelation and Minimum), which were associated with TMB level in NSCLC. A TMB prediction model consisting of 3 radiomic features was constructed by multiple logistic regression. The area under the curve (AUC) value in the TCGA training dataset was 0.816 (95% CI: 0.7109-0.9203) for predicting TMB level in NSCLC. The AUC value in external validation dataset I was 0.775 (95% CI: 0.5528-0.9972) for predicting TMB level in NSCLC, and the AUC value in external validation dataset II was 0.762 (95% CI: 0.5669-0.9569) for predicting the efficacy of immunotherapy in NSCLC. CONCLUSION: The model based on CT radiomic features helps to achieve cost effective improvement in TMB classification and precise immunotherapy treatment of NSCLC patients.

Exploring effective implementation pathways to become an excellent chief financial officer in public hospital: a qualitative comparative analysis (QCA) from China.

BACKGROUND: Hospital chief financial officer (CFO) contributes to improving health system performance. However, how to become an excellent hospital CFO has rarely been considered from a holistic perspective. This paper aims to identify competencies required by hospital CFO to fulfil the position's responsibilities and explore effective implementation pathways to generate high performance and improve healthcare service. METHODS: We conducted 61 semi-structured interviews with individuals in key leadership positions in China's hospitals and researchers focusing on healthcare system management to identify core competencies necessary for hospital CFO. Interviews were analysed through a multi-stage review process and modified via expert vetting using a national panel of 23 professors. Subsequently, interviews were conducted with 32 hospital CFOs from 14 provinces throughout September 2021 to May 2022. We scored the performance of 32 hospital CFOs in various aspects of competency and used the fuzzy-set qualitative comparative analysis to explore the competency configurations of excellent CFOs. RESULTS: We identify seven core competencies necessary for a hospital CFO to fulfil management practices, including personal morality, resource management, strategy management, learning ability, negotiating skill, leadership skill, and financial management. The findings indicate that a single competency factor is not a necessary condition to become an excellent hospital CFO. The results of qualitative comparative analysis then make it possible to propose four configurational paths, namely, supportive, interpersonal, all-around development, and technical, to become an excellent hospital CFO and achieve effective managerial performance. CONCLUSIONS: The responsibilities of hospital CFOs are complex and varied, hence, a better understanding of competencies required by CFO is essential to implement their responsibilities effectively. The identification in this study of the four effective implementation pathways to becoming an excellent hospital CFO enriches the literature on hospital management and provides implications for China's hospitals and their CFOs.

How does diagnosis-related group payment impact the health care received by rural residents? Lessons learned from China.

OBJECTIVES: There is growing evidence that differences exist between rural and urban residents in terms of health, access to care and the quality of health care received, especially in low- and middle-income countries (LMICs). To improve health equity and the performance of health systems, a diagnosis-related group (DRG) payment system has been introduced in many LMICs to reduce financial risk and improve the quality of health care. The aim of this study was to examine the impact of DRG payments on the health care received by rural residents in China, and to help policymakers identify and design implementation strategies for DRG payment systems for rural residents in LMICs. STUDY DESIGN: Health impact assessment. METHODS: This study compared the impact of DRG payments on the healthcare received by rural residents in China between the pre- and post-reform periods by applying a difference-in-difference (DID) methodology. The study population included individuals with three common conditions; namely, cerebral infarction, transient ischaemic attack (TIA), and vertebrobasilar insufficiency (VBI). Data on patient medical insurance type were assessed, and those who did not have rural insurance were excluded. RESULTS: This study included 13,088 patients. In total, 33.63% were from Guangdong (n = 4401), 38.21% were from Shandong (n = 5002), and 28.16% were from Guangxi (n = 3685). The DID results showed that the implementation of DRGs was positively associated with hospitalization expense (ß4 = 0.265, P = 0.000), treatment expense (ß4 = 0.343, P = 0.002), drug expense (ß4 = 0.607, P = 0.000), the spending of medical insurance funds (ß4 = 0.711, P = 0.000) and out-of-pocket costs (ß4 = 0.164, P = 0.000). CONCLUSIONS: The findings of this study suggest that the implementation of DRG payments increases health care costs and the financial burden on health systems and rural patients in LMICs. This is contrary to the original intention of implementing the DRG payment system.

Vehicle Occupant Detection Based on MM-Wave Radar.

With the continuous development of automotive intelligence, vehicle occupant detection technology has received increasing attention. Despite various types of research in this field, a simple, reliable, and highly private detection method is lacking. This paper proposes a method for vehicle occupant detection using millimeter-wave radar. Specifically, the paper outlines the system design for vehicle occupant detection using millimeter-wave radar. By collecting the raw signals of FMCW radar and applying Range-FFT and DoA estimation algorithms, a range-azimuth heatmap was generated, visually depicting the current status of people inside the vehicle. Furthermore, utilizing the collected range-azimuth heatmap of passengers, this paper integrates the Faster R-CNN deep learning networks with radar signal processing to identify passenger information. Finally, to test the performance of the detection method proposed in this article, an experimental verification was conducted in a car and the results were compared with those of traditional machine learning algorithms. The findings indicated that the method employed in this experiment achieves higher accuracy, reaching approximately 99%.

Energy-Efficient, Cluster-Based Routing Protocol for Wireless Sensor Networks Using Fuzzy Logic and Quantum Annealing Algorithm.

The main limitation of wireless sensor networks (WSNs) lies in their reliance on battery power. Therefore, the primary focus of the current research is to determine how to transmit data in a rational and efficient way while simultaneously extending the network's lifespan. In this paper, a hybrid of a fuzzy logic system and a quantum annealing algorithm-based clustering and routing protocol (FQA) is proposed to improve the stability of the network and minimize energy consumption. The protocol uses a fuzzy inference system (FIS) to select appropriate cluster heads (CHs). In the routing phase, we used the quantum annealing algorithm to select the optimal route from the CHs and the base station (BS). Furthermore, we defined an energy threshold to filter candidate CHs in order to save computation time. Unlike with periodic clustering, we adopted an on-demand re-clustering mechanism to perform global maintenance of the network, thereby effectively reducing the computation and overhead. The FQA was compared with FRNSEER, BOA-ACO, OAFS-IMFO, and FC-RBAT in different scenarios from the perspective of energy consumption, alive nodes, network lifetime, and throughput. According to the simulation results, the FQA outperformed all the other methods in all scenarios.

Effects of Bacillus-based inoculum on odor emissions co-regulation, nutrient element transformations and microbial community tropological structures during chicken manure and sawdust composting.

This study aims to evaluate whether different doses of Bacillus-based inoculum inoculated in chicken manure and sawdust composting will provide distinct effects on the co-regulation of ammonia (NH3) and hydrogen sulfide (H2S), nutrient conversions and microbial topological structures. Results indicate that the Bacillus-based inoculum inhibits NH3 emissions mainly by regulating bacterial communities, while promotes H2S emissions by regulating both bacterial and fungal communities. The inoculum only has a little effect on total organic carbon (TOC) and inhibits total sulfur (TS) and total phosphorus (TP) accumulations. Low dose inoculation inhibits total potassium (TK) accumulation, while high dose inoculation promotes TK accumulation and the opposite is true for total nitrogen (TN). The inoculation slightly affects the bacterial compositions, significantly alters the fungal compositions and increases the microbial cooperation, thus influencing the compost substances transformations. The microbial communities promote ammonium nitrogen (NH4+-N), TN, available phosphorus (AP), total potassium (TK) and TS, but inhibit nitrate nitrogen (NO3--N), TP and TK. Additionally, the bacterial communities promote, while the fungal communities inhibit the nitrite nitrogen (NO2--N) production. The core bacterial and fungal genera regulate NH3 and H2S emissions through the secretions of metabolic enzymes and the promoting or inhibiting effects on NH3 and H2S emissions are always opposite. Hence, Bacillus-based inoculum cannot regulate the NH3 and H2S emissions simultaneously.

UBE2C as an Immune-Related Biomarker for Breast Cancer: A Study Based on Multiple Databases.

Objective To screen the target gene UBE2C and explore its prognostic value and immune correlation in breast cancer (BRCA) using multiple databases. Methods The microarray expression datasets of BRCA were downloaded from the Gene Expresssion Omnibus database (GEO) and analyzed to obtain differentially expressed genes (DEGs). Hub genes were obtained by constructing and visualizing the protein-protein interaction network of DEGs. Then the key gene UBE2C was determined using R language, STRING, and Cytoscape, and the differential expression of UBE2C was verified using the external datasets, The Cancer Genome Atlas (TCGA) , and quantitative real-time PCR (qRT-PCR). The prognostic value and immunological correlation of UBE2C in BRCA were explored using R language, TIMER, and Gene Set Enrichment Analysis (GSEA).Results The expression of UBE2C was differentially upregulated in BRCA, as verified by TCGA and qRT-PCR. Prognostic analysis revealed that UBE2C served as an independent prognostic factor. High expression of UBE2C was associated with decreased immune infiltration levels of B cells, CD4+ T cells, CD8+ T cells, macrophages, and myeloid dendritic cells in BRCA tissue. The expression of UBE2C in BRCA showed a significant correlation with PDCD1, CD274, and CTLA4 expressions. There was a positive correlation between the expression of UBE2C and the tumor mutational burden and microsatellite instability. GSEA demonstrated that UBE2C expression significantly enriched 786 immune-related gene sets.Conclusions UBE2C expression in BRCA tissues can predict the survivals and prognosis of BRCA patients. Also, it is closely related to the BRCA immune microenvironment and can predict the effecacy of immunotherapy in BRCA patients. Therefore, UBE2C may be an potential immune-related prognostic biomarker for BRCA.

Combined Ultrasensitive Detection of Renal Cancer Proteins and Cells Using an Optical Microfiber Functionalized with Ti3C2 MXene and Gold Nanorod-Nanosensitized Interfaces.

The ultrasensitive and quantitative detection of renal cancer protein biomarkers present at ultralow concentrations for early-stage cancer diagnosis requires a biosensing probe possessing ultrahigh detection sensitivity and remarkable biosensing selectivity. Here, we report an optical microfiber integrated with Ti3C2-supported gold nanorod hybrid nanointerfaces for implementation in ultrasensitive sensing of the carbonic anhydrase IX (CAIX) protein and renal cancer cells. Because the evanescent field of the fiber is strongly coupled with nanointerfaces in the near-infrared region, the proposed optical microfiber biosensor achieves ultrahigh-sensitivity detection of the CAIX protein biomarker with ultralow limits of detection (LODs) of 13.8 zM in pure buffer solution and 0.19 aM in 30% serum solution. In addition, the proposed sensor also successfully and specifically recognizes living renal cancer cells in cell culture media with a LOD of 180 cells/mL. This strategy may serves as a powerful biosensing platform that combines the quantification of protein biomarkers and cancer cells, resulting in a higher accuracy of early-stage renal cancer diagnosis and screenings.

Chinese herb related molecules Catechins, Caudatin and Cucurbitacin-I inhibit the proliferation of glioblastoma by activating KDELR2-mediated endoplasmic reticulum stress.

Brain gliomas are difficult in the field of tumor therapy because of their high recurrence rate, high mortality rate, and low selectivity of therapeutic agents. The efficacy of Traditional Chinese Medicine (TCM) in the treatment for tumours has been widely recognized. Here, three Chinese herb related molecules, namely Catechins, Caudatin and Cucurbitacin-I, were screened by bioinformatic means, and were found to inhibit the proliferation of glioblastoma T98G cells using Colony-forming and CCK-8 assays. Notably, the simultaneous use of all three molecules could more significantly inhibit the proliferation of glioma cells. Consistent with this, temozolomide, each in the combination with three molecules, could synergistically inhibit the proliferation of T98G cells. Results of qPCR assay was also showed that this inhibition was through the activation of the KDELR2-mediated endoplasmic reticulum stress (ER) pathway. Molecular docking experiments further revealed that Catechins, Caudatin and Cucurbitacin-I could activate ER stress might by targeting KDELR2. Taken together, these results suggest that these herbal molecules have the potential to inhibit the growth of glioma cells and could provide a reference for clinical therapeutic drug selection.

Stretchable, Electrochemically-Stable Electrochromic Devices Based on Semi-Embedded Ag@Au Nanowire Network.

Stretchable electrochromic (EC) devices that can adapt the irregular and dynamic human surfaces show promising applications in wearable display, adaptive camouflage, and visual sensation. However, challenges exist in lacking transparent conductive electrodes with both tensile and electrochemical stability to assemble the complex device structure and endure harsh electrochemical redox reactions. Herein, a wrinkled, semi-embedded Ag@Au nanowire (NW) networks are constructed on elastomer substrates to fabricate stretchable, electrochemically-stable conductive electrodes. The stretchable EC devices are then fabricated by sandwiching a viologen-based gel electrolyte between two conductive electrodes with the semi-embedded Ag@Au NW network. Because the inert Au layer inhibits the oxidation of Ag NWs, the EC device exhibits much more stable color changes between yellow and green than those with pure Ag NW networks. In addition, since the wrinkled semi-embedded structure is deformable and reversibly stretched without serious fractures, the EC devices still maintain excellent color-changing stability under 40% stretching/releasing cycles.

Synergistic Interaction of Dual-Polymer Networks Containing Viologens-Anchored Poly(ionic liquid)s Enabling Long-Life and Large-Area Electrochromic Organogels.

Viologens-based electrochromic (EC) devices with multiple color changes, rapid response time, and simple all-in-one architecture have aroused much attention, yet suffer from poor redox stability caused by the irreversible aggregation of free radical viologens. Herein, the semi-interpenetrating dual-polymer network (DPN) organogels are introduced to improve the cycling stability of viologens-based EC devices. The primary cross-linked poly(ionic liquid)s (PILs) covalently anchored with viologens can suppress irreversible face-to-face contact between radical viologens. The secondary poly(vinylidenefluoride-co-hexafluoropropylene) (PVDF-HFP) chains with strong polar groups of -F can not only synergistically confine the viologens by the strong electrostatic effect, but also improve the mechanical performance of the organogels. Consequently, the DPN organogels show excellent cycling stability (87.5% retention after 10 000 cycles) and mechanical flexibility (strength of 3.67 MPa and elongation of 280%). Three types of alkenyl viologens are designed to obtain blue, green, and magenta colors, demonstrating the universality of the DPN strategy. Large-area EC devices (20 × 30 cm) and EC fibers based on organogels are assembled to demonstrate promising applications in green and energy-saving buildings and wearable electronics.

Efficacy and safety of rivaroxaban for the treatment of PICC-related upper extremity deep vein thrombosis in cancer patients: a retrospective study.

BACKGROUND: The optimal duration and choice of anticoagulant for the treatment of Peripherally inserted central catheters (PICC)-related upper extremity deep vein thrombosis (UEDVT) in cancer patients are still undetermined. OBJECTIVES: The aim of this study was to assess the efficacy and safety of rivaroxaban for the treatment of PICC-related UEDVT in cancer patients. METHODS: We conducted a retrospective cohort study including consecutive cancer patients for the management of acute symptomatic PICC-related UEDVT. The efficacy outcome of the study was the 180-day recurrence of any venous thromboembolism (VTE), while the safety outcome was the 180-day incidence of all bleeding events. The Kaplan‒Meier method was used to estimate the overall incidence. Hazard ratios (HRs) were obtained with a Cox proportional hazards model to estimate the risk of the outcome events. RESULTS: A total of 217 patients were included in the final analysis with a median age of 56 years old, 41.5% of whom had metastases. After the initial 3-5 days of nadroparin, patients received sequential anticoagulation, either with nadroparin (118 patients) or with rivaroxaban (99 patients). Four patients with recurrent VTE were observed (nadroparin, n = 2; rivaroxaban, n = 2). The 180-day cumulative VTE recurrence rates were 1.7% and 2.0% (p = 0.777) in patients receiving nadroparin and rivaroxaban, respectively. The overall bleeding rate at 180 days was 8.8%. Although no major bleeding events were observed, nineteen patients with clinically relevant nonmajor bleeding (CRNMB) were observed. The 180-day cumulative rate of CRNMB was 5.1% for nadroparin and 13.1% for rivaroxaban (HR = 3.303, 95% CI 1.149-9.497, p = 0.027). CONCLUSION: Our study supported the efficacy of rivaroxaban for treating PICC-related UEDVT in cancer patients. However, data on anticoagulation therapy for PICC-related UEDVT presented with a low risk of VTE recurrence and a relatively high risk of CRNMB bleeding events. Considering the risk-benefit ratio, further well-designed trials are required to optimize the drug selection and duration for the treatment of PICC-related UEDVT in cancer patients.

Dose-dependent early white matter alterations in patients with brain metastases after radiotherapy.

PURPOSE: Previous diffusion tensor imaging (DTI) studies have mainly focused on dose-dependent white matter (WM) alterations 1 month to 1 year after radiation therapy (RT) with a tract-average method. However, WM alterations immediately after RT are subtle, resulting in early WM alterations that cannot be detected by tract-average methods. Therefore, we performed a study with an along-tract method in patients with brain metastases to explore the early dose-response pattern of WM alterations after RT. METHODS: Sixteen patients with brain metastases underwent DTI before and 1-3 days after brain RT. DTI metrics, such as fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD), were calculated. Along-tract statistics were then used to resample WM fibre streamlines and generate a WM skeleton fibre tract. DTI metric alterations (post_RT-pre_RT DTI metrics) and the planned doses (max or mean doses) were mapped to 18 WM tracts. A linear fixed model was performed to analyse the main effect of dose on DTI metric alterations. RESULTS: AD alterations in the left hemispheric uncinated fasciculus (UNC_L) were associated with max doses, in which decreased AD alterations were associated with higher doses. CONCLUSION: Our findings may provide pathological insight into early dose-dependent WM alterations and may contribute to the development of max dose-constrained RT techniques to protect brain microstructure in the UNC_L.

KRAS status predicted by pretreatment MRI radiomics was associated with lung metastasis in locally advanced rectal cancer patients.

BACKGROUND: Mutated KRAS may indicate an invasive nature and predict prognosis in locally advanced rectal cancer (LARC). We aimed to establish a radiomic model using pretreatment T2W MRIs to predict KRAS status and explore the association between the KRAS status or model predictions and lung metastasis. METHODS: In this retrospective multicentre study, LARC patients from two institutions between January 2012 and January 2019 were randomly divided into training and testing cohorts. Least absolute shrinkage and selection operator (LASSO) regression and the support vector machine (SVM) classifier were utilized to select significant radiomic features and establish a prediction model, which was validated by radiomic score distribution and decision curve analysis. The association between the model stratification and lung metastasis was investigated by Cox regression and Kaplan‒Meier survival analysis; the results were compared by the log-rank test. RESULTS: Overall, 103 patients were enrolled (73 and 30 in the training and testing cohorts, respectively). The median follow-up was 38.1 months (interquartile range: 26.9, 49.4). The radiomic model had an area under the curve (AUC) of 0.983 in the training cohort and 0.814 in the testing cohort. Using a cut-off of 0.679 defined by the receiver operating characteristic (ROC) curve, patients with a high radiomic score (RS) had a higher risk for lung metastasis (HR 3.565, 95% CI 1.337, 9.505, p = 0.011), showing similar predictive performances for the mutant and wild-type KRAS groups (HR 3.225, 95% CI 1.249, 8.323, p = 0.016, IDI: 1.08%, p = 0.687; NRI 2.23%, p = 0.766). CONCLUSIONS: We established and validated a radiomic model for predicting KRAS status in LARC. Patients with high RS experienced more lung metastases. The model could noninvasively detect KRAS status and may help individualize clinical decision-making.

Exploring a competency framework for the chief financial officer of a hospital: a qualitative study from China.

BACKGROUND: Hospital chief financial officer (CFO) plays a vital role in supporting the effective management of organization. Understanding their competencies is essential to improve hospital development and health care services in China. This paper aims to explore competencies necessary for hospital CFOs to fulfil their management responsibilities and develop a competency framework for hospital CFOs in China. METHODS: A qualitative study was applied by conducting in-depth interviews with 151 participants from 15 Chinese provinces, comprising 89 individuals from 67 hospitals, and 62 individuals from 39 medical universities. Interviews were anonymised, recorded and transcribed. Qualitative thematic analysis was applied through a multi-stage review process and modified via the Delphi process using a national panel of 36 experts. RESULTS: Using content analysis, we identified 17 competencies organized into three themes (personal attitudes, leadership competencies and managerial competencies) to conduct a competency framework for hospital CFO to fulfil their management practices. Those competencies emphasized the integration of different competencies required by the hospital CFO. CONCLUSIONS: This paper identified the detailed expertise, abilities and personal traits required by hospital CFOs in China, expanding the insights and perspectives of hospital CFOs currently working in China to literature. The proposed framework will help hospitals establish selection criteria, coaching tools, and development plans for CFOs.

Ligand-displaying-exosomes using RNA nanotechnology for targeted delivery of multi-specific drugs for liver cancer regression.

Liver cancer such as hepatocellular carcinoma (HCC) poorly responds to chemotherapeutics as there are no effective means to deliver the drugs to liver cancer. Here we report GalNAc decorated exosomes as cargo for targeted delivery of Paclitaxel (PTX) and miR122 to liver tumors as an effective means to inhibit the HCC. Exosomes (Exos) are nanosized extracellular vesicles that deliver a payload to cancer cells effectively. GalNAc provides Exos targeting ability by binding to the asialoglycoprotein-receptor (ASGP-R) overexpressed on the liver cancer cell surface. A 4-way junction (4WJ) RNA nanoparticle was constructed to harbor 24 copies of hydrophobic PTX and 1 copy of miR122. The 4WJ RNA-PTX complex was loaded into the Exos, and its surface was decorated with GalNAc using RNA nanotechnology to obtain specific targeting. The multi-specific Exos selectively bind and efficiently delivered the payload into the liver cancer cells and exhibited the highest cancer cell inhibition due to the multi-specific effect of miR122, PTX, GalNAc, and Exos. The same was reflected in mice xenograft studies, the liver cancer was efficiently inhibited after systemic injection of the multi-specific Exos. The required effective dose of chemical drugs carried by Exos was significantly reduced, indicating high efficiency and low toxicity. The multi-specific strategy demonstrates that Exos can serve as a natural cargo vehicle for the targeted delivery of anticancer therapeutics to treat difficult-to-treat cancers.