Global prevalence of liver disease in human and domestic animals caused by Fasciola: A systematic review and meta-analysis.

Background: Liver disease caused by Fasciola is a significant zoonotic and parasitic disease with substantial economic impacts on humans and animals. Many studies have looked at the prevalence of fasciolis worldwide, yet the overall prevalence and risk factors in cattle, ruminants, and humans remains unknown. Methods: We conducted a systematic review and meta-analysis to estimate the global prevalence and risk factors of fascioliasis in humans and domestic ruminants. With this aim, we searched PubMed, ScienceDirect, Web of Science, and Scopus from inception to 8 December 2022 for studies reporting the prevalence of fascioliasis in humans or domestic ruminants post-2000. We then used random effects models to describe the prevalence of fascioliasis; trim-and-fill analysis and Egger's test to assess publication bias; and meta-regression and sensitivity analyses to examine the risk factors for prevalence and heterogeneity. Results: We retrieved 4422 articles, with 371 being included in the analysis, as they concerned fascioliasis in humans and ruminants globally. The pooled prevalence of bovine fasciolosis was 17%, while ovine fasciolosis and human fascioliasis had pooled prevalences of 13% and 5%, respectively. We also conducted subgroup analyses by continents, countries, Fasciola species, sampling years, altitude, rainfall, temperature, humidity, age, sex, feeding mode, and residence. Here, altitude and age emerged as risk factors associated with an increased prevalence of fascioliasis. Both the trim-and-fill analysis and Egger's test confirmed the presence of publication bias, while the sensitivity analysis showed that the omission of any single study did not significantly influence the combined pooled prevalence. Conclusions: Fascioliasis is a widely prevalent zoonosis among humans and livestock worldwide. Strategies targeting risk factors such as altitude and age are urgently needed for prevention and control of this disease, which will consequently reduce Fasciola infection. Additionally, given the inadequacy or absence of data in some countries, greater attention should be paid to Fasciola infection, with further epidemiological studies focussing on improving data quality.

Surgical resection and neoadjuvant therapy in patients with gastric cancer and ovarian metastasis: A real-world study.

BACKGROUND: Regarding when to treat gastric cancer and ovarian metastasis (GCOM) and whether to have metastatic resection surgery, there is presently debate on a global scale. The purpose of this research is to examine, in real-world patients with GCOM, the survival rates and efficacy of metastatic vs non-metastasized resection. AIM: To investigate the survival time and efficacy of metastatic surgery and neoadjuvant therapy in patients with GCOM. METHODS: This study retrospectively analyzed the data of 41 GCOM patients admitted to Zhejiang Provincial People's Hospital from June 2009 to July 2023. The diagnosis of all patients was confirmed by pathology. The primary study endpoints included overall survival (OS), ovarian survival, OS after surgery (OSAS), disease-free survival (DFS), differences in efficacy. RESULTS: This study had 41 patients in total. The surgical group (n = 27) exhibited significantly longer median OS (mOS) and median overall months (mOM) compared to the nonoperative group (n = 14) (mOS: 23.0 vs 6.9 months, P = 0.015; mOM: 18.3 vs 3.8 months, P = 0.001). However, there were no significant differences observed in mOS, mOM, median OSAS (mOSAS), and median DFS (mDFS) between patients in the surgical resection plus neoadjuvant therapy group (n = 11) and those who surgical resection without neoadjuvant therapy group (n = 16) (mOS: 26.1 months vs 21.8 months, P = 0.189; mOM: 19.8 vs 15.2 months, P = 0.424; mOSAS: 13.9 vs 8.7 months, P = 0.661, mDFS: 5.1 vs 8.2 months, P = 0.589). CONCLUSION: Compared to the non-surgical group, the surgical group's survival duration and efficacy are noticeably longer. The efficacy and survival time of the direct surgery group and the neoadjuvant therapy group did not differ significantly.

The Asymmetrical Fe-O-Se Bonds in Fe2O(SeO3)2 Boosting Bifunctional Oxygen Electrocatalytic Performance for Zinc-Air Battery.

Here Fe2O(SeO3)2/Fe3C@NC catalysts with high performance were fabricated for zinc-air batteries (ZABs). The experimental results confirmed that the existence of Fe-O-Se bonds in Fe2O(SeO3)2 crystal phase, and the Fe-O-Se bonds could obviously enhance ORR and OER catalytic performance of Fe2O(SeO3)2/Fe3C@NC. Density functional theoretical calculations (DFT) confirmed that the Fe2O(SeO3)2 in Fe2O(SeO3)2/Fe3C@NC had a higher d-band center of Fe atom and a lower p-orbital coupling degree with its own lattice O atom than Fe2O3, which leads to Fe site of Fe2O(SeO3)2 being more likely to adsorb external oxygen intermediates. The Fe-O-Se bonds in Fe2O(SeO3)2 results in the modification of coordination environment of Fe atoms and optimizes the adsorption energy of Fe site for oxygen intermediates. Compared with Fe2O3/Fe3C@NC, the Fe2O(SeO3)2/Fe3C@NC showed obvious enhancements of ORR/OER catalytic activities with a half-wave potential of 0.91 V for ORR in 0.1 M KOH electrolyte and a low overpotential of 345 mV for OER at 10 mA cm-2 in a 1.0 M KOH electrolyte. The peak power density and specific capacity of Fe2O(SeO3)2/Fe3C@NC-based ZABs are higher than those of Pt/C+RuO2-ZABs. The above results demonstrate that the asymmetrical Fe-O-Se bonds in Fe2O(SeO3)2 plays a key role in improving the bifunctional catalytic activities of ORR/OER for ZABs.

Tumor immune microenvironment of NSCLC with EGFR exon 20 insertions may predict efficacy of first-line ICI-combined regimen.

OBJECTIVES: Non-small cell lung cancer (NSCLC) patients with exon 20 insertion mutations (ex20ins) of the epidermal growth factor receptor (EGFR) were resistant to monotherapy of immune checkpoint inhibitor (ICI). However, recent reports have shown that the combination of ICI and chemotherapy (ICI-combined regimen) exhibited certain efficacy for NSCLC with EGFR ex20ins. The mechanisms behind this phenomenon have not been thoroughly clarified. Hence, we conducted this study tofind correlations between the tumor immune microenvironment of EGFR ex20ins and the efficacy of ICI-combined regimen. METHODS: We performed single-cell transcriptome sequencing and multiplex immunofluorescence staining (mIF) to investigate the immune microenvironment of NSCLC patients with EGFR ex20ins, L858R, and EGFR wild-type. We analyzed 15 treatment-naïve NSCLC samples utilizing single-cell RNA sequencing (scRNA-seq). Another 30 cases of EGFR L858R and 4 cases of wild-type were recruited to compare the immune microenvironment with that of EGFR ex20ins (28 cases) by mIF. RESULTS: We observed that cell components, function and interactions varied between EGFR ex20ins, L858R, and wild-type NSCLC.We discovered similar T cell and CD8+ T cell distributions among groups but found noninferior or even better T cell activation in ex20ins patients. Infiltrating CD8+ FOXP3- T cells were significantly lower in the tumor region of EGFR ex20ins compared to wild-type. T cells from the ex20ins group had a greater tendency to promote cancer cell inflammation and epithelial-mesenchymal transition (EMT) compared to wild-type group. For macrophages, there were more M2-like macrophages in ex20ins patients. M1-like macrophages in ex20ins group produced fewer antitumor cytokines than in other groups. CONCLUSIONS: The immune microenvironment of EGFR ex20ins is more suppressive than that of L858R and wild-type, suggesting that ICI monotherapy may not be sufficient for these patients. ICI-combined regimen might be a treatment option for EGFR ex20ins due to tumor-promoting inflammation and noninferior T cell functions in the immune microenvironment.

Regio- and enantioselective nickel-alkyl catalyzed hydroalkylation of alkynes.

The migratory insertion of metal-hydride into alkene has allowed regioselective access to organometallics, readily participating in subsequent functionalization as one conventional pathway of hydroalkylation, whereas analogous process with feedstock alkyne is drastically less explored. Among few examples, the regioselectivity of metal-hydride insertion is mostly governed by electronic bias of alkynes. To alter the regioselectivity and drastically expand the intermediate pools that we can access, one aspirational design is through alternative nickel-alkyl insertion, providing opposite regioselectivity induced by steric demand. Leveraging in situ formed nickel-alkyl species, we herein report the regio- and enantioselective hydroalkylation of alkynes with broad functional group tolerance, excellent regio- and enantioselectivity, enabling efficient route to diverse valuable chiral allylic amines motifs. Preliminary mechanistic studies indicate the aminoalkyl radical species can participate in metal-capture and lead to formation of nickel-alkyl, of which the migratory insertion is key to reverse regioselectivity observed in metal-hydride insertion.

Improving quantitative prediction of protein subcellular locations in fluorescence images through deep generative models.

Machine learning has been employed in recognizing protein localization at the subcellular level, which highly facilitates the protein function studies, especially for those multi-label proteins that localize in more than one organelle. However, existing works mostly study the qualitative classification of protein subcellular locations, ignoring fraction of one multi-label protein in different locations. Actually, about 50 % proteins are multi-label proteins, and the ignorance of quantitative information highly restricts the understanding of their spatial distribution and functional mechanism. One reason of the lack of quantitative study is the insufficiency of quantitative annotations. To address the data shortage problem, here we proposed a generative model, PLocGAN, which could generate cell images with conditional quantitative annotation of the fluorescence distribution. The model was a conditional generative adversarial network, in which the condition learning utilized partial label learning to overcome the lack of training labels and allowed training with only qualitative labels. Meanwhile, it used contrastive learning to enhance diversity of the generated images. We assessed the PLocGAN on four pixel-fused synthetic datasets and one real dataset, and demonstrated that the model could generate images with good fidelity and diversity, outperforming existing state-of-the-art generative methods. To verify the utility of PLocGAN in the quantitative prediction of protein subcellular locations, we replaced the training images with generated quantitative images and built prediction models, and found that they had a boosting effect on the quantitative estimation. This work demonstrates the effectiveness of deep generative models in bioimage analysis, and provides a new solution for quantitative subcellular proteomics.

Murine exosomal miR-30a aggravates cardiac function after acute myocardial infarction via regulating cell fate of cardiomyocytes and cardiac resident macrophages.

After acute myocardial infarction (AMI), intercellular communication is crucial for maintaining cardiac homeostasis and patient survival. Exosomes secreted by cardiomyocytes serve as carriers for transporting microRNA(miRNAs), participating in intercellular signaling and the regulation of cardiac function. This study aims to investigate the role of exosomal microRNA-30a(miR-30a) during AMI and its underlying mechanisms. AMI was induced by permanent ligation of the left anterior descending (LAD) artery in C57BL/6 mice. The expression of miR-30a in mice was respectively enhanced and inhibited by administering agomiR-30a and antagomiR-30a. Using HL-1 cardiomyocytes and RAW264.7 macrophages for in vitro experiments, HL-1 cardiomyocytes were cultured under hypoxic conditions to induce ischemic injury. Following isolation and injection of exosomals, a variety of validation methods were utilized to assess the expression of miR-30a, and investigate the effects of enriched exosomal miR-30a on the state of cardiomyocytes. After AMI, the level of exosomal miR-30a in the serum of mice significantly increased and was highly enriched in cardiac tissue. Cardiomyocytes treated with agomiR-30a and miR-30a-enriched exosomes exhibited inhibition of cell autophagy, increased cell apoptosis, mice showed an larger myocardial infarct area and poorer cardiac function. Exosomes released from hypoxic cardiomyocytes transferred miR-30a to cardiac resident macrophages, promoting the polarization into pro-inflammatory M1 macrophages. In conclusion, murine exosomal miR-30a exacerbates cardiac dysfunction post-AMI by disrupting the autophagy-apoptosis balance in cardiomyocytes and polarizing cardiac resident macrophages into pro-inflammatory M1 macrophages. Modulating the expression of miR-30a may reduce cardiac damage following AMI, and targeting exosomal miR-30a could be a potential therapeutic approach for AMI.

Computed tomography-based radiomics machine learning models for differentiating enchondroma and atypical cartilaginous tumor in long bones.

To explore the value of CT-based radiomics machine learning models for differentiating enchondroma from atypical cartilaginous tumor (ACT) in long bones and methods to improve model performance.59 enchondromas and 53 ACTs in long bones confirmed by pathology were collected retrospectively. The features were extracted from preoperative CT images of these patients, and least absolute shrinkage and selection operator (LASSO) regression was used for feature selection and dimensionality reduction. The selected features were used to construct classification models by thirteen machine learning algorithms. The data set was randomly divided into a training set and a test set at a proportion of 7:3 by ten-fold cross-validation to evaluate the performance of these models.A total of 1199 features were extracted, 9 features were selected, and 13 radiomics machine learning models were constructed. The area under the curve (AUC) of 11 models was more than 0.8, and that of 3 models was more than 0.9. The Extremely Randomized Trees model achieved the best performance (AUC = 0.9375 ± 0.0884), followed by the Adaptive Boosting model (AUC = 0.9188 ± 0.1010) and the Linear Discriminant Analysis model (AUC = 0.9062 ± 0.1459).CT-based radiomics machine learning models had great ability to distinguish enchondroma and ACT in long bones. By using filters to deeply mine high-order features in the original image and selecting appropriate machine learning algorithms, the performance of the model can be improved. · CT-based radiomics machine learning models can distinguish enchondroma and ACT in long bones.. · Using filters and selecting advanced machine learning algorithms can improve model performance.. · Clinical features have limited utility in distinguishing enchondroma and ACT in long bones.. · Hong R, Li Q, Ma J et al. Computed tomography-based radiomics machine learning models for differentiating enchondroma and atypical cartilaginous tumor in long bones. Fortschr Röntgenstr 2024; DOI 10.1055/a-2344-5398.

Glycomol: A pervasive tool for structure predication of natural saponin products basing on MS data.

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Sponge-derived alkaloid AP-7 as a sensitizer to cisplatin in the treatment of multidrug-resistant NSCLC via Chk1-dependent mechanisms.

Multidrug resistance is a substantial obstacle in treating non-small cell lung cancer (NSCLC) with therapies like cisplatin (DDP)-based adjuvant chemotherapy and EGFR-tyrosine kinase inhibitors (TKIs). Aaptamine-7 (AP-7), a benzonaphthyridine alkaloid extracted from Aaptos aaptos sponge, has been shown to exhibit a broad spectrum of anti-tumor activity. However, the anti-cancer activity of AP-7 in combination with DDP and its molecular mechanisms in multidrug-resistant NSCLC are not yet clear. Our research indicates that AP-7 bolsters the growth inhibition activity of DDP on multidrug-resistant NSCLC cells. AP-7 notably disrupts DDP-induced cell cycle arrest and amplifies DDP-induced DNA damage effects in these cells. Furthermore, the combination of AP-7 and DDP downregulates Chk1 activation, interrupts the DNA damage repair-dependent Chk1/CDK1 pathway, and helps to overcome drug resistance and boost apoptosis in multidrug-resistant NSCLC cells and a gefitinib-resistant xenograft mice model. In summary, AP-7 appears to enhance DDP-induced DNA damage by impeding the Chk1 signaling pathway in multidrug-resistant NSCLC, thereby augmenting growth inhibition, both in vitro and in vivo. These results indicate the potential use of AP-7 as a DDP sensitizer in the treatment of multidrug-resistant NSCLC.

Amorphous P-CoOX Promotes the Formation of Hypervalent Ni Species in NiFe LDHs by Amorphous/Crystalline Interfaces for Excellent Catalytic Performance of Oxygen Evolution Reaction.

Water electrolysis has become an attractive hydrogen production method. Oxygen evolution reaction (OER) is a bottleneck of water splitting as its four-electron transfer procedure presents sluggish reaction kinetics. Designing composite catalysts with high performance for efficient OER still remains a huge challenge. Here, the P-doped cobalt oxide/NiFe layered double hydroxides (P-CoOX/NiFe LDHs) composite catalysts with amorphous/crystalline interfaces are successfully prepared for OER by hydrothermal-electrodeposition combined method. The results of electrochemical characterizations, operando Raman spectra, and DFT theoretical calculations have demonstrated the electrons in the P-CoOX/NiFe LDHs heterointerfaces are easily transferred from Ni2+ to Co3+ because that the amorphous configuration of P-CoOX can well induce Ni-O-Co orbital coupling. The electron transfer of Ni2+ to the surrounding Fe3+ and Co3+ will lead to the unoccupied eg orbitals of Ni3+ that can promote water dissociation and accelerate *OOH migration to improve OER catalytic performance. The optimized P-CoOX/NiFe LDHs exhibit superior catalytic performance for OER with a very low overpotential of 265 mV at 300 mA cm-2 and excellent long-term stability of 500 h with almost no attenuation at 100 mA cm-2. This work will provide a new method to design high-performance NiFe LDHs-based catalysts for OER.

Direct detection Φ-OTDR based on UWFBG array using linear-phase-modulated double-pulse.

We propose what we believe to be a novel direct detection phase-sensitive optical time-domain reflectometry (Φ-OTDR) based on ultra-weak fiber Bragg grating (UWFBG) array to achieve distributed vibration measurements with exceptional sensitivity and remarkable stability. Our system employs a pulse modulator to generate a double pulse and achieves linear phase modulation of one pulse by one cycle through a phase modulator. The phase change can be quantitatively demodulated using our proposed N-step phase-shifted demodulation algorithm. This method effectively mitigates the influence of phase noise of the laser and the pulse modulator, while also eliminating fluctuations in the half-voltage of the phase modulator. Compared with the existing phase modulation methods, our method avoids stringent requirements for the stability and precision of phase modulation. Moreover, we propose a phase-shifted approximation method, breaking the limitation of sensing length on the traditional differential approximation method and improving the accuracy significantly. The technique's effectiveness is experimentally demonstrated on a 1 km UWFBG array with a reflectivity of -40 dB to -45 dB and a spatial resolution of 10 m. Vibrations with different amplitudes are measured quantitatively with good linearity. The low-frequency self-noise is greatly suppressed and the overall self-noise is -54.3 dB rad2/Hz.

BCAT1 alleviates early brain injury by inhibiting ferroptosis through PI3K/AKT/mTOR/GPX4 pathway after subarachnoid hemorrhage.

Regulation of the redox system by branched-chain amino acid transferase 1 (BCAT1) is of great significance in the occurrence and development of diseases, but the relationship between BCAT1 and subarachnoid hemorrhage (SAH) is still unknown. Ferroptosis, featured by iron-dependent lipid peroxidation accompanied by the depletion of glutathione peroxidase 4 (GPX4), has been implicated in the pathological process of early brain injury after subarachnoid hemorrhage. This study established SAH model by endovascular perforation and adding oxyhemoglobin (Hb) to HT22 cells and delved into the mechanism of BCAT1 in SAH-induced ferroptotic neuronal cell death. It was found that SAH-induced neuronal ferroptosis could be inhibited by BCAT1 overexpression (OE) in rats and HT22 cells, and BCAT1 OE alleviated neurological deficits and cognitive dysfunction in rats after SAH. In addition, the effect of BCAT1 could be reversed by the Ly294002, a specific inhibitor of the PI3K pathway. In summary, our present study indicated that BCAT1 OE alleviated early brain injury EBI after SAH by inhibiting neuron ferroptosis via activation of PI3K/AKT/mTOR pathway and the elevation of GPX4. These results suggested that BCAT1 was a promising therapeutic target for subarachnoid hemorrhage.

Complement system is overactivated in patients with IgA nephropathy after COVID-19.

IgA nephropathy (IgAN), which has been confirmed as a complement mediated autoimmune disease, is also one form of glomerulonephritis associated with COVID-19. Here, we aim to investigate the clinical and immunological characteristics of patients with IgAN after COVID-19. The level of plasma level of C5a (p < 0.001), soluble C5b-9 (p = 0.018), FHR5 (p < 0.001) were all significantly higher in Group CoV (33 patients with renal biopsy-proven IgAN experienced COVID-19) compared with Group non-CoV (44 patients with IgAN without COVID-19), respectively. Compared with Group non-CoV, the intensity of glomerular C4d (p = 0.017) and MAC deposition (p < 0.001) and Gd-IgA1 deposition (p = 0.005) were much stronger in Group CoV. Our finding revealed that for IgAN after COVID-19, mucosal immune responses to SARS-CoV-2 infection may result in the overactivation of systemic and renal local complement system, and increased glomerular deposition of Gd-IgA1, which may lead to renal dysfunction and promote renal progression in IgAN patients.

CARD11-BCL10-MALT1 Complex-Dependent MALT1 Activation Facilitates Myocardial Oxidative Stress in Doxorubicin-Treated Mice via Enhancing k48-Linked Ubiquitination of Nrf2.

Aims: Downregulation of nuclear factor erythroid 2-related factor 2 (Nrf2) contributes to doxorubicin (DOX)-induced myocardial oxidative stress, and inhibition of mucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT1) increased Nrf2 protein level in rat heart suffering ischemia/reperfusion, indicating a connection between MALT1 and Nrf2. This study aims to explore the role of MALT1 in DOX-induced myocardial oxidative stress and the underlying mechanisms. Results: The mice received a single injection of DOX (15 mg/kg, i.p.) to induce myocardial oxidative stress, evidenced by increases in the levels of reactive oxidative species as well as decreases in the activities of antioxidative enzymes, concomitant with a downregulation of Nrf2; these phenomena were reversed by MALT1 inhibitor. Similar phenomena were observed in DOX-induced oxidative stress in cardiomyocytes. Mechanistically, knockdown or inhibition of MALT1 notably attenuated the interaction between Nrf2 and MALT1 and decreased the k48-linked ubiquitination of Nrf2. Furthermore, inhibition or knockdown of calcium/calmodulin-dependent protein kinase II (CaMKII-δ) reduced the phosphorylation of caspase recruitment domain-containing protein 11 (CARD11), subsequently disrupted the assembly of CARD11, B cell lymphoma 10 (BCL10), and MALT1 (CBM) complex, and reduced the MALT1-dependent k48-linked ubiquitination of Nrf2 in DOX-treated mice or cardiomyocytes. Innovation and Conclusion: The E3 ubiquitin ligase function of MALT1 accounts for the downregulation of Nrf2 and aggravation of myocardial oxidative stress in DOX-treated mice, and CaMKII-δ-dependent phosphorylation of CARD11 triggered the assembly of CBM complex and the subsequent activation of MALT1.

A noradrenergic pathway for the induction of pain by sleep loss.

An epidemic of sleep loss currently affects modern societies worldwide and is implicated in numerous physiological disorders, including pain sensitization, although few studies have explored the brain pathways affected by active sleep deprivation (ASD; e.g., due to recreation). Here, we describe a neural circuit responsible for pain sensitization in mice treated with 9-h non-stress ASD. Using a combination of advanced neuroscience methods, we found that ASD stimulates noradrenergic inputs from locus coeruleus (LCNA) to glutamatergic neurons of the hindlimb primary somatosensory cortex (S1HLGlu). Moreover, artificial inhibition of this LCNA→S1HLGlu pathway alleviates ASD-induced pain sensitization in mice, while chemogenetic activation of this pathway recapitulates the pain sensitization observed following ASD. Our study thus implicates activation of the LCNA→S1HLGlu pathway in ASD-induced pain sensitization, expanding our fundamental understanding of the multisystem interplay involved in pain processing.

Predicting major adverse cardiovascular events within 3 years by optimization of radiomics model derived from pericoronary adipose tissue on coronary computed tomography angiography: a case-control study.

BACKGROUND: Coronary inflammation induces changes in pericoronary adipose tissue (PCAT) can be detected by coronary computed tomography angiography (CCTA). Our aim was to investigate whether different PCAT radiomics model based on CCTA could improve the prediction of major adverse cardiovascular events (MACE) within 3 years. METHODS: This retrospective study included 141 consecutive patients with MACE and matched to patients with non-MACE (n = 141). Patients were randomly assigned into training and test datasets at a ratio of 8:2. After the robust radiomics features were selected by using the Spearman correlation analysis and the least absolute shrinkage and selection operator, radiomics models were built based on different machine learning algorithms. The clinical model was then calculated according to independent clinical risk factors. Finally, an overall model was established using the radiomics features and the clinical factors. Performance of the models was evaluated for discrimination degree, calibration degree, and clinical usefulness. RESULTS: The diagnostic performance of the PCAT model was superior to that of the RCA-model, LAD-model, and LCX-model alone, with AUCs of 0.723, 0.675, 0.664, and 0.623, respectively. The overall model showed superior diagnostic performance than that of the PCAT-model and Cli-model, with AUCs of 0.797, 0.723, and 0.706, respectively. Calibration curve showed good fitness of the overall model, and decision curve analyze demonstrated that the model provides greater clinical benefit. CONCLUSION: The CCTA-based PCAT radiomics features of three major coronary arteries have the potential to be used as a predictor for MACE. The overall model incorporating the radiomics features and clinical factors offered significantly higher discrimination ability for MACE than using radiomics or clinical factors alone.

A clinical-radiomics nomogram based on spectral CT multi-parameter images for preoperative prediction of lymph node metastasis in colorectal cancer.

To develop a clinical-radiomics nomogram based on spectral CT multi-parameter images for predicting lymph node metastasis in colorectal cancer. A total of 76 patients with colorectal cancer and 156 lymph nodes were included. The clinical data of the patients were collected, including gender, age, tumor location and size, preoperative tumor markers, etc. Three sets of conventional images in the arterial, venous, and delayed phases were obtained, and six sets of spectral images were reconstructed using the arterial phase spectral data, including virtual monoenergetic images (40 keV, 70 keV, 100 keV), iodine density maps, iodine no water maps, and virtual non-contrast images. Radiomics features of lymph nodes were extracted from the above images, respectively. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to select features. A clinical model was constructed based on age and carcinoembryonic antigen (CEA) levels. The radiomics features selected were used to generate a composed radiomics signature (Com-RS). A nomogram was developed using age, CEA, and the Com-RS. The models' prediction efficiency, calibration, and clinical application value were evaluated by the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis, respectively. The nomogram outperforms the clinical model and the Com-RS (AUC = 0.879, 0.824). It is well calibrated and has great clinical application value. This study developed a clinical-radiomics nomogram based on spectral CT multi-parameter images, which can be used as an effective tool for preoperative personalized prediction of lymph node metastasis in colorectal cancer.

Fe-Doped Ni2P/NiSe2 Composite Catalysts for Urea Oxidation Reaction (UOR) for Energy-Saving Hydrogen Production by UOR-Assisted Water Splitting.

The development of efficient urea oxidation reaction (UOR) catalysts helps UOR replace the oxygen evolution reaction (OER) in hydrogen production from water electrolysis. Here, we prepared Fe-doped Ni2P/NiSe2 composite catalyst (Fe-Ni2P/NiSe2-12) by using phosphating-selenizating and acid etching to increase the intrinsic activity and active areas. Spectral characterization and theoretical calculations demonstrated that electrons flowed through the Ni-P-Fe-interface-Ni-Se-Fe, thus conferring high UOR activity to Fe-Ni2P/NiSe2-12, which only needed 1.39 V vs RHE to produce the current density of 100 mA cm-2. Remarkably, this potential was 164 mV lower than that required for the OER under the same conditions. Furthermore, EIS demonstrated that UOR driven by the Fe-Ni2P/NiSe2-12 exhibited faster interfacial reactions, charge transfer, and current response compared to OER. Consequently, the Fe-Ni2P/NiSe2-12 catalyst can effectively prevent competition with OER and NSOR, making it suitable for efficient hydrogen production in UOR-assisted water electrolysis. Notably, when water electrolysis is operated at a current density of 40 mA cm-2, this UOR-assisted system can achieve a decrease of 140 mV in the potential compared to traditional water electrolysis. This study presents a novel strategy for UOR-assisted water splitting for energy-saving hydrogen production.

RNAi efficiency is enhanced through knockdown of double-stranded RNA-degrading enzymes in butterfly Papilio xuthus.

The efficiency of RNA interference (RNAi) has always limited the research on the phenotype innovation of Lepidoptera insects. Previous studies have found that double-stranded RNA-degrading enzyme (dsRNase) is an important factor in RNAi efficiency, but there have been no relevant reports in butterflies (Papilionoidea). Papilio xuthus is one of the important models in butterflies with an extensive experimental application value. To explore the effect of dsRNase in the RNAi efficiency on butterflies, six dsRNase genes (PxdsRNase 1-6) were identified in P. xuthus genome, and their dsRNA-degrading activities were subsequently detected by ex vivo assays. The result shows that the dsRNA-degrading ability of gut content (<1 h) was higher than hemolymph content (>12 h). We then investigated the expression patterns of these PxdsRNase genes during different tissues and developmental stages, and related RNAi experiments were carried out. Our results show that different PxdsRNase genes had different expression levels at different developmental stages and tissues. The expression of PxdsRNase2, PxdsRNase3, and PxdsRNase6 were upregulated significantly through dsGFP injection, and PxdsRNase genes can be silenced effectively by injecting their corresponding dsRNA. RNAi-of-RNAi studies with PxEbony, which acts as a reporter gene, observed that silencing PxdsRNase genes can increase RNAi efficiency significantly. These results confirm that silencing dsRNase genes can improve RNAi efficiency in P. xuthus significantly, providing a reference for the functional study of insects such as butterflies with low RNAi efficiency.