Machine learning-based decision support model for selecting intra-arterial therapies for unresectable hepatocellular carcinoma: A national real-world evidence-based study.

IMPORTANCE: Intra-arterial therapies(IATs) are promising options for unresectable hepatocellular carcinoma(HCC). Stratifying the prognostic risk before administering IAT is important for clinical decision-making and for designing future clinical trials. OBJECTIVE: To develop and validate a machine learning(ML)-based decision support model(MLDSM) for recommending IAT modalities for unresectable HCC. DESIGN, SETTING, AND PARTICIPANTS: Between October 2014 and October 2022, a total of 2,959 patients with HCC who underwent initial IATs were enroled retrospectively from 13 tertiary hospitals. These patients were divided into the training cohort (n = 1700), validation cohort (n = 428), and test cohort (n = 200). MAIN OUTCOMES AND MEASURES: Thirty-two clinical variables were input, and five supervised ML algorithms, including eXtreme Gradient Boosting (XGBoost), Categorical Gradient Boosting (CatBoost), Gradient Boosting Decision Tree (GBDT), Light Gradient Boosting Machine (LGBM) and Random Forest (RF), were compared using the areas under the receiver operating characteristic curve (AUC) with the DeLong test. RESULTS: A total of 1856 patients were assigned to the IAT alone Group(I-A), and 1103 patients were assigned to the IAT combination Group(I-C). The 12-month death rates were 31.9% (352/1103) in the I-A group and 50.4% (936/1856) in the I-C group. For the test cohort, in the I-C group, the CatBoost model achieved the best discrimination when 30 variables were input, with an AUC of 0.776 (95% confidence intervals [CI], 0.833-0.868). In the I-A group, the LGBM model achieved the best discrimination when 24 variables were input, with an AUC of 0.776 (95% CI, 0.833-0.868). According to the decision trees, BCLC grade, local therapy, and diameter as top three variables were used to guide clinical decisions between IAT modalities. CONCLUSIONS AND RELEVANCE: The MLDSM can accurately stratify prognostic risk for HCC patients who received IATs, thus helping physicians to make decisions about IAT and providing guidance for surveillance strategies in clinical practice.

Epidermal growth factor-loaded, dehydrated physical microgel-formed adhesive hydrogel enables integrated care of wet wounds.

Integrated wound care, a sequential process of promoting wound hemostasis, sealing, and healing, is of great clinical significance. However, the wet environment of wounds poses formidable challenges for integrated care. Herein, we developed an epidermal growth factor (EGF)-loaded, dehydrated physical microgel (DPM)-formed adhesive hydrogel for the integrated care of wet wounds. The DPMs were designed using the rational combination of hygroscopicity and reversible crosslinking of physical hydrogels. Unlike regular bioadhesives, which consider interfacial water as a barrier to adhesion, DPMs utilize water to form desirable adhesive structures. The hygroscopicity allowed the DPMs to absorb interfacial water and subsequently, the interfacial adhesion was realized by the interactions between tissue and DPMs. The reversible crosslinks further enabled DPMs to integrate into hydrogels (DPM-Gels), thus achieving wet adhesion. Importantly, the water-absorbing gelation mode of DPMs enabled facile loading of biologically active EGF to promote wound healing. We demonstrated that the DPM-Gels possessed wet tissue adhesive performance, with about 40 times the wet adhesive strength of fibrin glue and about 4 times the burst pressure of human blood pressure. Upon application at the injury site, the EGF-loaded DPM-Gels sequentially promoted efficient wound hemostasis, stable sealing, and quick healing, achieving integrated care of wet wounds.

Variability in soybean yield responses to elevated atmospheric CO2: Insights from non-structural carbohydrate remobilisation during seed filling.

The increasing atmospheric CO2 concentration (e[CO2]) has mixed effects on soybean most varieties' yield. This study elucidated the effect of e[CO2] on soybean yield and the underlying mechanisms related to photosynthetic capacity, non-structural carbohydrate (NSC) accumulation, and remobilisation. Four soybean cultivars were cultivated in open-top chambers at two CO2 levels. Photosynthesis rates were determined from R2 to R6. Plants were sampled at R5 and R8 to determine carbohydrate concentrations. There were significant variations in yield responses among the soybean cultivars under e[CO2], from no change in DS1 to a 22% increase in SN14. DS1 and SN14 had the smallest and largest increase, respectively, in daily carbon assimilation capacity. Under e[CO2], DS1, MF5, and XHJ had an increase in Ci, at which point the transition from Rubisco-limited to ribulose-1,5-bisphosphate regeneration-limited photosynthesis occurred, in contrast with SN14. Thus, the cultivars might have distinct mechanisms that enhance photosynthesis under e[CO2] conditions. A positive correlation was between daily carbon assimilation response to e[CO2] and soybean yield, emphasising the importance of enhanced photosynthate accumulation before the R5 stage in determining yield response to e[CO2]. E[CO2] significantly influenced NSC accumulation in vegetative organs at R5, with variation among cultivars. There was enhanced NSC remobilisation during seed filling, indicating cultivar-specific responses to the remobilisation of sucrose and soluble sugars, excluding sucrose and starch. A positive correlation was between leaf and stem NSC remobilisation and yield response to e[CO2], emphasising the role of genetic differences in carbohydrate remobilisation mechanisms in determining soybean yield variation under elevated CO2 levels.

A Novel Machine Learning Model for Predicting Stroke-Associated Pneumonia After Spontaneous Intracerebral Hemorrhage.

BACKGROUND: Pneumonia is one of the most common complications after spontaneous intracerebral hemorrhage (sICH), i.e., stroke-associated pneumonia (SAP). Timely identification of targeted patients is beneficial to reduce poor prognosis. So far, there is no consensus on SAP prediction, and application of existing predictors is limited. The aim of this study was to develop a machine learning model to predict SAP after sICH. METHODS: We retrospectively reviewed 748 patients diagnosed with sICH and collected data from 4 dimensions-demographic features, clinical features, medical history, and laboratory tests. Five machine learning algorithms-logistic regression, gradient boosting decision tree, random forest, extreme gradient boosting, and category boosting-were used to build and validate the predictive model. We also applied recursive feature elimination with cross-validation to obtain the best feature combination for each model. Predictive performance was evaluated by area under the receiver operating characteristic curve. RESULTS: SAP was diagnosed in 237 patients. The model developed by category boosting yielded the most satisfactory outcomes overall with area under the receiver operating characteristic curves in the training set and test set of 0.8307 and 0.8178, respectively. CONCLUSIONS: The incidence of SAP after sICH in our center was 31.68%. Machine learning could potentially provide assistance in the prediction of SAP after sICH.

Development and evaluation of machine learning models for predicting large-for-gestational-age newborns in women exposed to radiation prior to pregnancy.

INTRODUCTION: The correlation between radiation exposure before pregnancy and abnormal birth weight has been previously proven. However, for large-for-gestational-age (LGA) babies in women exposed to radiation before becoming pregnant, there is no prediction model yet. MATERIAL AND METHODS: The data were collected from the National Free Preconception Health Examination Project in China. A sum of 455 neonates (42 SGA births and 423 non-LGA births) were included. A training set (n = 319) and a test set (n = 136) were created from the dataset at random. To develop prediction models for LGA neonates, conventional logistic regression (LR) method and six machine learning methods were used in this study. Recursive feature elimination approach was performed by choosing 10 features which made a big contribution to the prediction models. And the Shapley Additive Explanation model was applied to interpret the most important characteristics that affected forecast outputs. RESULTS: The random forest (RF) model had the highest average area under the receiver-operating-characteristic curve (AUC) for predicting LGA in the test set (0.843, 95% confidence interval [CI]: 0.714-0.974). Except for the logistic regression model (AUC: 0.603, 95%CI: 0.440-0.767), other models' AUCs displayed well. Thereinto, the RF algorithm's final prediction model using 10 characteristics achieved an average AUC of 0.821 (95% CI: 0.693-0.949). CONCLUSION: The prediction model based on machine learning might be a promising tool for the prenatal prediction of LGA births in women with radiation exposure before pregnancy.

Tissue-adhesive, stretchable and compressible physical double-crosslinked microgel-integrated hydrogels for dynamic wound care.

Integrated wound care through sequentially promoting hemostasis, sealing, and healing holds great promise in clinical practice. However, it remains challenging for regular bioadhesives to achieve integrated care of dynamic wounds due to the difficulties in adapting to dynamic mechanical and wet wound environments. Herein, we reported a type of dehydrated, physical double crosslinked microgels (DPDMs) which were capable of in situ forming highly stretchable, compressible and tissue-adhesive hydrogels for integrated care of dynamic wounds. The DPDMs were designed by the rational integration of the reversible crosslinks and double crosslinks into micronized gels. The reversible physical crosslinks enabled the DPDMs to integrate together, and the double crosslinked characteristics further strengthen the formed macroscopical networks (DPDM-Gels). We demonstrated that the DPDM-Gels simultaneously possess outstanding tensile (∼940 kJ/m3) and compressive (∼270 kJ/m3) toughness, commercial bioadhesives-comparable tissue-adhesive strength, together with stable performance under hundreds of deformations. In vivo results further revealed that the DPDM-Gels could effectively stop bleeding in various bleeding models, even in an actual dynamic environment, and enable the integrated care of dynamic skin wounds. On the basis of the remarkable mechanical and appropriate adhesive properties, together with impressive integrated care capacities, the DPDM-Gels may provide a new approach for the smart care of dynamic wounds. STATEMENT OF SIGNIFICANCE: Integrated care of dynamic wounds holds great significance in clinical practice. However, the dynamic and wet wound environments pose great challenges for existing hydrogels to achieve it. This work developed robust adhesive hydrogels for integrated care of dynamic wounds by designing dehydrated, physical double crosslinked microgels (DPDMs). The reversible and double crosslinks enabled DPDMs to integrate into macroscopic hydrogels with high mechanical properties, appropriate adhesive strength and stable performance under hundreds of external deformations. Upon application at the injury site, DPDM-Gels efficiently stopped bleeding, even in an actual dynamic environment and showed effectiveness in integrated care of dynamic wounds. With the fascinating properties, DPDMs may become an effective tool for smart wound care.

Learning to Holistically Detect Bridges From Large-Size VHR Remote Sensing Imagery.

Bridge detection in remote sensing images (RSIs) plays a crucial role in various applications, but it poses unique challenges compared to the detection of other objects. In RSIs, bridges exhibit considerable variations in terms of their spatial scales and aspect ratios. Therefore, to ensure the visibility and integrity of bridges, it is essential to perform holistic bridge detection in large-size very-high-resolution (VHR) RSIs. However, the lack of datasets with large-size VHR RSIs limits the deep learning algorithms' performance on bridge detection. Due to the limitation of GPU memory in tackling large-size images, deep learning-based object detection methods commonly adopt the cropping strategy, which inevitably results in label fragmentation and discontinuous prediction. To ameliorate the scarcity of datasets, this paper proposes a large-scale dataset named GLH-Bridge comprising 6,000 VHR RSIs sampled from diverse geographic locations across the globe. These images encompass a wide range of sizes, varying from 2,048 × 2,048 to 16,384 × 16,384 pixels, and collectively feature 59,737 bridges. These bridges span diverse backgrounds, and each of them has been manually annotated, using both an oriented bounding box (OBB) and a horizontal bounding box (HBB). Furthermore, we present an efficient network for holistic bridge detection (HBD-Net) in large-size RSIs. The HBD-Net presents a separate detector-based feature fusion (SDFF) architecture and is optimized via a shape-sensitive sample re-weighting (SSRW) strategy. The SDFF architecture performs inter-layer feature fusion (IFF) to incorporate multi-scale context in the dynamic image pyramid (DIP) of the large-size image, and the SSRW strategy is employed to ensure an equitable balance in the regression weight of bridges with various aspect ratios. Based on the proposed GLH-Bridge dataset, we establish a bridge detection benchmark including the OBB and HBB tasks, and validate the effectiveness of the proposed HBD-Net. Additionally, cross-dataset generalization experiments on two publicly available datasets illustrate the strong generalization capability of the GLH-Bridge dataset. The dataset and source code will be released at https://luo-z13.github.io/GLH-Bridge-page/.

Se Alleviated Pb-Caused Neurotoxicity in Chickens: SPS2-GPx1-GSH-IL-2/IL-17-NO Pathway, Selenoprotein Suppression, Oxidative Stress, and Inflammatory Injury.

Lead (Pb), a heavy metal environmental pollutant, poses a threat to the health of humans and birds. Inflammation is one of the most common pathological phenomena in the case of illness and poisoning. However, the underlying mechanisms of inflammation remain unclear. The cerebellum and the thalamus are important parts of the nervous system. To date, there have been no reports of Pb inducing inflammation in animal cerebellums or thalami. Selenium (Se) can relieve Pb poisoning. Therefore, we aimed to explore the mechanism by which Se alleviates Pb toxicity to the cerebellums and thalami of chickens by establishing a chicken Pb or/and Se treatment model. Our results demonstrated that exposure to Pb caused inflammatory damage in cerebellums and thalami, evidenced by the characteristics of inflammation, the decrease in anti-inflammatory factors (interleukin (IL)-2 and interferon-γ (INF-γ)), and the increase in pro-inflammatory factors (IL-4, IL-6, IL-12ß, IL-17, and nitric oxide (NO)). Moreover, we found that the IL-2/IL-17-NO pathway took part in Pb-caused inflammatory injury. The above findings were reversed by the supplementation of dietary Se, meaning that Se relieved inflammatory damage caused by Pb via the IL-2/IL-17-NO pathway. In addition, an up-regulated oxidative index malondialdehyde (MDA) and two down-regulated antioxidant indices (glutathione (GSH) and total antioxidant capacity (TAC)) were recorded after the chickens received Pb stimulation, indicating that excess Pb caused an oxidant/antioxidant imbalance and oxidative stress, and the oxidative stress mediated inflammatory damage via the GSH-IL-2 axis. Interestingly, exposure to Pb inhibited four glutathione peroxidase (GPx) family members (GPx1, GPx2, GPx3, and GPx4), three deiodinase (Dio) family members (Dio1, Dio2, and Dio3), and fifteen other selenoproteins (selenophosphate synthetase 2 (SPS2), selenoprotein (Sel)H, SelI, SelK, SelM, SelO, SelP1, SelPb, SelS, SelT, SelU, and selenoprotein (Sep)n1, Sepw1, Sepx1, and Sep15), suggesting that Pb reduced antioxidant capacity and resulted in oxidative stress involving the SPS2-GPx1-GSH pathway. Se supplementation, as expected, reversed the changes mentioned above, indicating that Se supplementation improved antioxidant capacity and mitigated oxidative stress in chickens. For the first time, we discovered that the SPS2-GPx1-GSH-IL-2/IL-17-NO pathway is involved in the complex inflammatory damage mechanism caused by Pb in chickens. In conclusion, this study demonstrated that Se relieved Pb-induced oxidative stress and inflammatory damage via the SPS2-GPx1-GSH-IL-2/IL-17-NO pathway in the chicken nervous system. This study offers novel insights into environmental pollutant-caused animal poisoning and provides a novel theoretical basis for the detoxification effect of Se against oxidative stress and inflammation caused by toxic pollutants.

Long Non-Coding RNA-Cardiac-Inducing RNA 6 Mediates Repair of Infarcted Hearts by Inducing Mesenchymal Stem Cell Differentiation into Cardiogenic Cells through Cyclin-Dependent Kinase 1.

This study aims to investigate the induction effect of LncRNA-CIR6 on MSC differentiation into cardiogenic cells in vitro and in vivo. In addition to pretreatment with Ro-3306 (a CDK1 inhibitor), LncRNA-CIR6 was transfected into BMSCs and hUCMSCs using jetPRIME. LncRNA-CIR6 was further transfected into the hearts of C57BL/6 mice via 100 µL of AAV9-cTnT-LncRNA-CIR6-ZsGreen intravenous injection. After three weeks of transfection followed by AMI surgery, hUCMSCs (5 × 105/100 µL) were injected intravenously one week later. Cardiac function was evaluated using VEVO 2100 and electric mapping nine days after cell injection. Immunofluorescence, Evans blue-TTC, Masson staining, FACS, and Western blotting were employed to determine relevant indicators. LncRNA-CIR6 induced a significant percentage of differentiation in BMSCs (83.00 ± 0.58)% and hUCMSCs (95.43 ± 2.13)% into cardiogenic cells, as determined by the expression of cTnT using immunofluorescence and FACS. High cTNT expression was observed in MSCs after transfection with LncRNA-CIR6 by Western blotting. Compared with the MI group, cardiac contraction and conduction function in MI hearts treated with LncRNA-CIR6 or combined with MSCs injection groups were significantly increased, and the areas of MI and fibrosis were significantly lower. The transcriptional expression region of LncRNA-CIR6 was on Chr17 from 80209290 to 80209536. The functional region of LncRNA-CIR6 was located at nucleotides 0-50/190-255 in the sequence. CDK1, a protein found to be related to the proliferation and differentiation of cardiomyocytes, was located in the functional region of the LncRNA-CIR6 secondary structure (from 0 to 17). Ro-3306 impeded the differentiation of MSCs into cardiogenic cells, while MSCs transfected with LncRNA-CIR6 showed a high expression of CDK1. LncRNA-CIR6 mediates the repair of infarcted hearts by inducing MSC differentiation into cardiogenic cells through CDK1.

Nanoparticles transfected with plasmid-encoded lncRNA-OIP5-AS1 inhibit renal ischemia-reperfusion injury in mice via the miR-410-3p/Nrf2 axis.

Nanostructures composed of liposomes and polydopamine (PDA) have demonstrated efficacy as carriers for delivering plasmids, effectively alleviating renal cell carcinoma. However, their role in acute kidney injury (AKI) remains unclear. This study aimed to investigate the effects of the plasmid-encoded lncRNA-OIP5-AS1@PDA nanoparticles (POP-NPs) on renal ischemia/reperfusion (RI/R) injury and explore the underlying mechanisms. RI/R or OGD/R models were established in mice and HK-2 cells, respectively. In vivo, vector or POP-NPs were administered (10 nmol, IV) 48 h after RI/R treatment. In the RI/R mouse model, the OIP5-AS1 and Nrf2/HO-1 expressions were down-regulated, while miR-410-3p expression was upregulated. POP-NPs treatment effectively reversed RI/R-induced renal tissue injury, restoring altered levels of blood urea nitrogen, creatinine, malondialdehyde, inflammatory factors (IL-8, IL-6, TNF-α), ROS, apoptosis, miR-410-3p, as well as the suppressed expression of SOD and Nrf2/HO-1 in the model mice. Similar results were obtained in cell models treated with POP-NPs. Additionally, miR-410-3p mimics could reverse the effects of POP-NPs on cellular models, partially counteracted by Nrf2 agonists. The binding relationship between OIP5-AS1 and miR-410-3p, alongside miR-410-3p and Nrf2, has been substantiated by dual-luciferase reporter and RNA pull-down assays. The study revealed that POP-NPs can attenuate RI/R-induced injury through miR-410-3p/Nrf2 axis. These findings lay the groundwork for future targeted therapeutic approaches utilizing nanoparticles for RI/R-induced AKI.

The Z-Scheme MIL-88B(Fe)/BiOBr Heterojunction Promotes Fe(III)/Fe(II) Cycling and Photocatalytic-Fenton-Like Synergistically Enhances the Degradation of Ciprofloxacin.

The Z-scheme MIL-88B/BiOBr (referred to as MxBy, whereas x and y are the mass of MIL-88B(Fe) and BiOBr) heterojunction photocatalysts are successfully prepared by a facile ball milling method. By adding low concentration H2O2 under visible light irradiation, the Z-scheme heterojunction and photocatalytic-Fenton-like reaction synergistically enhance the degradation and mineralization of ciprofloxacin (CIP). Among them, M50B150 showed efficient photodegradation efficiency and excellent cycling stability, with 94.6% removal of CIP (10 mg L-1) by M50B150 (0.2 g L-1) under 90 min of visible light. In the MxBy heterojunctions, the rapid transfer of photo-generated electrons not only directly decomposed H2O2 to generate ·OH, but also improved the cycle of Fe3+/Fe2+ pairs, which facilitated the reaction with H2O2 to generate ·OH and ·O2 - radicals. In addition, the effects of photocatalyst dosages, pH of CIP solution, and coexisting substances on CIP removal are systematically investigated. It is found that the photocatalytic- Fenton-like reaction can be carried out at a pH close to neutral conditions. Finally, the charge transfer mechanism of the Z-scheme is verified by electron spin resonance (ESR) signals. The ecotoxicity of CIP degradation products is estimated by the T.E.S.T tool, indicating that the constructed photocatalysis-Fenton-like system is a green wastewater treatment technology.

Double-Solvent-Induced Derivatization of Bi-MOF to Vacancy-Rich Bi4O5Br2: Toward Efficient Photocatalytic Degradation of Ciprofloxacin in Water and HCHO Gas.

MOF-derived photocatalytic materials have potential in degrading ciprofloxacin (CIP) in water and HCHO gas pollutants. Novel derivatization means and defect regulation are effective techniques for improving the performance of MOF-derived photocatalysis. Vacancy-rich Bi4O5Br2 (MBO-x) were derived in one step from Bi-MOF (CAU-17) by a modified double-solvent method. MBO-50 produced more oxygen vacancies due to the combined effect of the CAU-17 precursor and double solvents. The photocatalytic performance of MBO was evaluated by degrading CIP and HCHO. Thanks to the favorable morphology and vacancy structure, MBO-50 demonstrated the best photocatalytic efficiency, with 97.0% removal of CIP (20 mg L-1) and 90.1% removal of HCHO (6.5 ppm) at 60 min of light irradiation. The EIS Nyquist measurement, transient photocurrent response, photoluminescence spectra, and the calculation of energy band information indicated that the vacancy sites can effectively capture photoexcited electrons during the charge transfer process, thus limiting the recombination of electrons and holes, improving the energy band structure, and making it easier to produce superoxide anion radical (·O2-) and to degrade CIP and HCHO. The improvement of photocatalytic performance of MBO-50 in HCHO degradation due to the bromine vacancy generation and filling mechanism was discussed in detail. This work provides a promising new idea for the modulation of MOF-derived photocatalytic materials.

Ion imprinted polymers integrated into a multi-functional microfluidic paper-based analytical device for trace cadmium detection in water.

A novel multi-functional microfluidic paper-based analytical device (µPAD) integrated with ion imprinted polymers (IIPs) was proposed for specific, portable and low-cost detection of cadmium (Cd(II)) in water. The IIP was grafted on paper and integrated into the µPAD for separation of Cd(II) through multi-layer design. The paper-based screen printed carbon electrode (pSPCE) modified with reduced graphene oxide was fabricated and combined with the µPAD for electrochemical sensing of the separated Cd(II). Reduced graphene oxide (rGO) was prepared via electroreduction on the working electrode surface of the pSPCE (rGO/pSPCE), which provided a sensitization effect with an improved signal for Cd(II) detection. The µPAD developed with the integrated IIP and combined with rGO/pSPCE is able to detect Cd(II) with a linear range from 1 ng ml-1 to 100 ng ml-1 and a detection limit of 0.05 ng ml-1. The accuracy of this µPAD was evaluated with spiked real water samples and compared with that of the inductively coupled plasma mass spectrometry (ICP-MS) method, from which the recovery values ranged from 96.5% to 114.2% with RSDs <10% between the two methods. This µPAD demonstrated its advantages of low-cost, portability, and suitability for highly sensitive detection of Cd(II), making it a valuable tool for on-site analysis.

An Electrochemical Sensor Based on Three-Dimensional Porous Reduced Graphene and Ion Imprinted Polymer for Trace Cadmium Determination in Water.

Three-dimensional (3D) porous graphene-based materials have displayed attractive electrochemical catalysis and sensing performances, benefiting from their high porosity, large surface area, and excellent electrical conductivity. In this work, a novel electrochemical sensor based on 3D porous reduced graphene (3DPrGO) and ion-imprinted polymer (IIP) was developed for trace cadmium ion (Cd(II)) detection in water. The 3DPrGO was synthesized in situ at a glassy carbon electrode (GCE) surface using a polystyrene (PS) colloidal crystal template and the electrodeposition method. Then, IIP film was further modified on the 3DPrGO by electropolymerization to make it suitable for detecting Cd(II). Attributable to the abundant nanopores and good electron transport of the 3DPrGO, as well as the specific recognition for Cd(II) of IIP, a sensitive determination of trace Cd(II) at PoPD-IIP/3DPrGO/GCE was achieved. The proposed sensor exhibited comprehensive linear Cd(II) responses ranging from 1 to 100 µg/L (R2 = 99.7%). The limit of detection (LOD) was 0.11 µg/L, about 30 times lower than the drinking water standard set by the World Health Organization (WHO). Moreover, PoPD-IIP/3DPrGO/GCE was applied for the detection of Cd(II) in actual water samples. The satisfying recoveries (97-99.6%) and relative standard deviations (RSD, 3.5-5.7%) make the proposed sensor a promising candidate for rapid and on-site water monitoring.

Paenibacillus polygoni sp. nov., an endophytic bacterium isolated from Polygonum lapathifolium L. in wetland.

A Gram-stain-positive, aerobic, rod-shaped, non-motile, yellowish and glossy strain, C31T, was isolated from a wetland plant Polygonum lapathifolium L. located south of Poyang Lake, Jiangxi Province, PR China. Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain C31T showed similarity values of lower than 97.0 % to other type species belonging to the genus Paenibacillus. The genomic average nucleotide identity values between strain C31T and its reference type species ranged from 68.9-70.9 % and the digital DNA-DNA hybridization values were lower than 27.8 %. The genomic DNA G+C content of strain C31T was 41.9 mol%. The optimal growth temperature, pH and NaCl concentration were 37 °C, pH 7 and 0.5 %, respectively. The major cellular fatty acids (>5.0 %) of strain C31T were anteiso-C15 : 0 (73.7 %), anteiso-C17 : 0 (8.4 %) and iso-C15 : 0 (5.2 %). The polar lipids of strain C31T were diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine and unidentified phospholipids. The respiratory quinone was MK-7. Based on these phylogenetic and phenotypic characterizations, strain C31T represents a novel species within the genus Paenibacillus. Therefore, the proposed name for this newly identified species is Paenibacillus polygoni sp. nov. and the type strain is C31T (=CCTCC AB 2022349T=KCTC 43565T).

Application of a modified osteotomy and positioning integrative template system (MOPITS) based on a truncatable reconstruction model in the precise mandibular reconstruction with fibula free flap: a pilot clinical study.

BACKGROUND: Mandibular defects can greatly affect patients' appearance and functionality. The preferred method to address this issue is reconstructive surgery using a fibular flap. The current personalized guide plate can improve the accuracy of osteotomy and reconstruction, but there are still some problems such as complex design process and time-consuming. Therefore, we modified the conventional template to serve the dual purpose of guiding the mandible and fibula osteotomy and facilitating the placement of the pre-bent titanium. METHODS: The surgery was simulated preoperatively using Computer-Aided Design (CAD) technology. The template and truncatable reconstruction model were produced in the laboratory using 3D printing. After pre-bending the titanium plate according to the contour, the reconstruction model was truncated and the screw trajectory was transferred to form a modified osteotomy and positioning integrative template system (MOPITS). Next, the patient underwent a composite template-guided vascularized fibula flap reconstruction of the mandible. All cases were reviewed for the total operative time and accuracy of surgery. RESULTS: The procedures involved 2-4 fibular segments in 15 patients, averaging 3 fibular segments per procedure. The osteotomy error is 1.01 ± 1.02 mm, while the reconstruction angular error is 1.85 ± 1.69°. The preoperative and postoperative data were compared, and both p > 0.05. During the same operation, implant placement was performed on four patients, with an average operative time of 487.25 ± 60.84 min. The remaining malignant tumor patients had an average operative time of 397.18 ± 73.09 min. The average postoperative hospital stay was 12.95 ± 3.29 days. CONCLUSIONS: This study demonstrates the effectiveness of MOPITS in facilitating precise preoperative planning and intraoperative execution of fibula flap reconstruction. MOPITS represents a promising and reliable tool for reconstructive surgery, particularly for inexperienced surgeons navigating the challenges of mandible defect reconstruction.

Conversion of steppe to cropland increases spatial heterogeneity of soil functional genes.

The microbiome function responses to land use change are important for the long-term prediction and management of soil ecological functions under human influence. However, it has remains uncertain how the biogeographic patterns of soil functional composition change when transitioning from natural steppe soils (NS) to agricultural soils (AS). We collected soil samples from adjacent pairs of AS and NS across 900 km of Mollisol areas in northeast China, and the soil functional composition was characterized using shotgun sequencing. AS had higher functional alpha-diversity indices with respect to KO trait richness and a higher Shannon index than NS. The distance-decay slopes of functional gene composition were steeper in AS than in NS along both spatial and environmental gradients. Land-use conversion from steppe to farmland diversified functional gene profiles both locally and spatially; it increased the abundances of functional genes related to labile carbon, but decreased those related to recalcitrant substrate mobilization (e.g., lignin), P cycling, and S cycling. The composition of gene functional traits was strongly driven by stochastic processes, while the degree of stochasticity was higher in NS than in AS, as revealed by the neutral community model and normalized stochasticity ratio analysis. Alpha-diversity of core functional genes was strongly related to multi-nutrient cycling in AS, suggesting a key relationship to soil fertility. The results of this study challenge the paradigm that the conversion of natural to agricultural habitat will homogenize soil properties and biology while reducing local and regional gene functional diversity.

The comparison of three different molecular imaging methods in localization and grading of insulinoma.

Aims: This cross-sectional study compared the value of molecular imaging (Exendin-4 positron emission tomography/computed tomography [PET/CT], 68Ga-DOTATATE PET/CT, 18F- fluorodeoxyglucose [FDG] PET/CT) in insulinoma localization by stratified tumor size and grading, and explored the correlation of the related the maximum standardized uptake value (SUVmax) with insulinoma grading, Ki-67, maximum tumor diameter, and glucose metabolism. Methods: In 28 insulinoma patients, the sensitivity of three types of PET/CT for localizing insulinoma was calculated according to tumor size and grade. We compared the SUVmax for different insulinoma grades and analyzed the correlation of SUVmax with Ki-67, maximum tumor diameter, and glucose metabolism indicators. Results: The study included 12 grade (G) 1 and 16 G2 cases, with maximum tumor diameters ranging from 9 to 40 mm. Without differentiation by size and grade, the sensitivity of Exendin-4 PET/CT to localize insulinoma was 100%, which significantly exceeded that of 68Ga-DOTATATE PET/CT and 18F-FDG PET/CT (75% and 57%, respectively). In tumors with a maximum diameter ≤ 20 mm and ≤ 15 mm, the sensitivity of Exendin-4 (both 100%) significantly exceeded that of 68Ga-DOTATATE PET/CT (74% and 64%, respectively) and 18F-FDG PET/CT (54% and 50%, respectively). In G1 tumors, the sensitivity of Exendin-4 PET/CT was significantly higher than that of 18F-FDG PET/CT, but not that of 68Ga-DOTATATE PET/CT, while in G2 tumors, the sensitivity of Exendin-4 PET/CT was significantly higher than that of both other types. However, all three PET/CT types missed a metastatic lymph node in one patient. The 18F-FDG PET/CT SUVmax was significantly lower than that of the other PET/CT types and that of 68Ga-DOTATATE PET/CT was significantly lower in G2 than in G1. 68Ga-DOTATATE PET/CT SUVmax correlated negatively with Ki-67. A receiver operating characteristic (ROC) curve suggested that 68Ga-DOTATATE PET/CT SUVmax > 19.9 could predict G1 tumors. Conclusion: Exendin-4 PET/CT was superior to 68Ga-DOTATATE PET/CT and 18F-FDG PET/CT for insulinoma localization, particularly small and G2 tumors, but its diagnostic value in small metastatic lymph nodes requires further exploration. 68Ga-DOTATATE PET/CT SUVmax could be used as an adjunct to pathology, and a value > 19.9 could predict G1 tumors. No PET/CT SUVmax could predict tumor maximum diameter and glucose metabolism.

Stimulation of primed carbon under climate change corresponds with phosphorus mineralization in the rhizosphere of soybean.

Elevated CO2 and temperature likely alter photosynthetic carbon inputs to soils, which may stimulate soil microbial activity to accelerate the decomposition of soil organic carbon (SOC), liberating more phosphorus (P) into the soil solution. However, this hypothesis on the association of SOC decomposition and P transformation in the plant rhizosphere requires robust soil biochemical evidence, which is critical to nutrient management for the mitigation of soil quality against climate change. This study investigated the microbial functional genes relevant to P mineralization together with priming processes of SOC in the rhizosphere of soybean grown under climate change. Soybean plants were grown under elevated CO2 (eCO2, 700 ppm) combined with warming (+ 2 °C above ambient temperature) in open-top chambers. Photosynthetic carbon flow in the plant-soil continuum was traced with 13CO2 labeling. The eCO2 plus warming treatment increased the primed carbon (C) by 43 % but decreased the NaHCO3-extratable organic P by 33 %. Furthermore, NaHCO3-Po was negatively correlated with phosphatase activity and microbial biomass C. Elevated CO2 increased the abundances of C degradation genes, such as abfA and ManB, and P mineralization genes, such as gcd, phoC and phnK. The results suggested that increased photosynthetic carbon inputs to the rhizosphere of plants under eCO2 plus warming stimulated the microbial population and metabolic functions of both SOC and organic P mineralization. There is a positive relationship between the rhizosphere priming effect and P mineralization. The response of microorganisms to plant-C flow is decisive for coupled C and P cycles, which are likely accelerated under climate change.

PET imaging of new target CDK19 in prostate cancer.

PURPOSE: Prostate-specific membrane antigen (PSMA)-positron emission tomography (PET) is a superior method to predict patients' risk of cancer progression and response to specific therapies. However, its performance is limited for neuroendocrine prostate cancer (NEPC) and PSMA-low prostate cancer cells, resulting in diagnostic blind spots. Hence, identifying novel specific targets is our aim for diagnosing those prostate cancers with low PSMA expression. METHODS: The Cancer Genome Atlas (TCGA) database and our cohorts from men with biopsy-proven high-risk metastatic prostate cancer were used to identify CDK19 and PSMA expression. PDX lines neP-09 and P-16 primary cells were used for cellular uptake and imaging mass cytometry in vitro. To evaluate in vivo CDK19-specific uptake of gallium(Ga)-68-IRM-015-DOTA, xenograft mice models and blocking assays were used. PET/CT imaging data were obtained to estimate the absorbed dose in organs. RESULTS: Our study group had reported the overexpression of a novel tissue-specific gene CDK19 in high-risk metastatic prostate cancer and CDK19 expression correlated with metastatic status and tumor staging, independently with PSMA and PSA levels. Following up on this new candidate for use in diagnostics, small molecules targeting CDK19 labeled with Ga-68 (68Ga-IRM-015-DOTA) were used for PET in this study. We found that the 68Ga-IRM-015-DOTA was specificity for prostate cancer cells, but the other cancer cells also took up little 68Ga-IRM-015-DOTA. Importantly, mouse imaging data showed that the NEPC and CRPC xenografts exhibited similar signal strength with 68Ga-IRM-015-DOTA, but 68Ga-PSMA-11 only stained the CRPC xenografts. Furthermore, target specificity was elucidated by a blocking experiment on a CDK19-bearing tumor xenograft. These data concluded that 68Ga-CDK19 PET/CT was an effective technology to detect lesions with or without PSMA in vitro, in vivo, and in the PDX model. CONCLUSION: Thus, we have generated a novel PET small molecule with predictive value for prostate cancer. The findings indicate that 68Ga-CDK19 may merit further evaluation as a predictive biomarker for PET scans in prospective cohorts and may facilitate the identification of molecular types of prostate cancer independent of PSMA.