m6A methyltransferase AflIme4 orchestrates mycelial growth, development and aflatoxin B1 biosynthesis in Aspergillus flavus

Aflatoxin B1 (AFB1), a highly toxic secondary metabolite produced by Aspergillus flavus, poses a severe threat to agricultural production, food safety and human health. The methylation of mRNA m6A has been identified as a regulator of both the growth and AFB1 production of A. flavus. However, its intracellular occurrence and function needs to be elucidated. Here, we identified and characterized a m6A methyltransferase, AflIme4, in A. flavus. The enzyme was localized in the cytoplasm, and knockout of AflIme4 significantly reduced the methylation modification level of mRNA. Compared with the control strains, ΔAflIme4 exhibited diminished growth, conidial formation, mycelial hydrophobicity, sclerotium yield, pathogenicity and increased sensitivity to CR, SDS, NaCl and H2O2. Notably, AFB1 production was markedly inhibited in the A. flavus ΔAflIme4 strain. RNA-Seq coupled with RT-qPCR validation showed that the transcriptional levels of genes involved in the AFB1 biosynthesis pathway including aflA, aflG, aflH, aflK, aflL, aflO, aflS, aflV and aflY were significantly upregulated. Methylated RNA immunoprecipitation-qPCR (MeRIP-qPCR) analysis demonstrated a significant increase in m6A methylation modification levels of these pathway-specific genes, concomitant with a decrease in mRNA stability. These results suggest that AflIme4 attenuates the mRNA stability of genes in AFB1 biosynthesis by enhancing their mRNA m6A methylation modification, leading to impaired AFB1 biosynthesis. Our study identifies a novel m6A methyltransferase AflIme4 and highlights it as a potential target to control A. flavus growth, development and aflatoxin pollution.

RNA-seq combined network pharmacology reveals that Fu-Gan-Wan (FGW) inhibits liver fibrosis via NF-κB/CCL2/CCR2 and lipid peroxidation via Nrf2/HMOX1 signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Liver fibrosis is a serious complication of liver disease characterized by excessive collagen deposition, without effective therapeutic agents in the clinic. Fu-Gan-Wan (FGW) is an empirical formula used for the clinical treatment of hepatitis and cirrhosis. It has been shown to reverse experimental liver fibrosis. However, its corresponding mechanisms remain unclear.

AIM OF THE REVIEW

This study aimed to elucidate the key pathways and target genes of FGW in attenuating liver fibrosis.

MATERIALS AND METHODS

The therapeutic effects of different doses of FGW on liver fibrosis were investigated using a 2 mL/kg 15% CCl4-induced mouse model. Then, RNA-seq combined with network pharmacology was used to analyze the key biological processes and signaling pathways underlying the anti-liver fibrosis exertion of FGW. These findings were validated in a TGF-β1-induced model of activation and proliferation of mouse hepatic stellate cell line JS-1. Finally, the key signaling pathways and molecular targets were validated using animal tissues, and the effect of FGW on tissue lipid peroxidation was additionally observed.

RESULTS

We found that 19.5 g/kg FGW significantly down-regulated CCl4-induced elevation of hepatic ALT and AST, decreased collagen deposition, and inhibited the expression of pro-fibrotic factors α-SMA, COL1α1, CTGF, TIMP-1, as well as pro-inflammatory factor TGF-β1. Additionally, FGW at doses of 62.5, 125, and 250 μg/mL dose-dependently blocked JS-1 proliferation, migration, and activation. Furthermore, RNA-seq identified the NF-κB signaling pathway as a key target molecular pathway for FGW against liver fibrosis, and network pharmacology combined with RNA-seq focused on 11 key genes. Significant changes were identified in CCL2 and HMOX1 by tissue RT-PCR, Western blot, and immunohistochemistry. We further demonstrated that FGW significantly attenuated CCl4-induced increases in p-p65, CCL2, CCR2, and HMOX1, while significantly elevating Nrf2. Finally, FGW significantly suppressed the accumulation of lipid peroxidation products MDA and 4-HNE and reconfigured the oxidation-reduction balance, including promoting the increase of antioxidants GPx, GSH, and SOD, and the decrease of peroxidation products ROS and GSSG.

CONCLUSIONS

This study demonstrated that FGW exhibits potential in mitigating CCl4-induced hepatic fibrosis, lipid peroxidation, and iron metabolism disorders in mice. This effect may be mediated through the NF-κB/CCL2/CCR2 and Nrf2/HMOX1 pathways.

Sub-region based radiomics analysis for prediction of isocitrate dehydrogenase and telomerase reverse transcriptase promoter mutations in diffuse gliomas

AIM

To enhance the prediction of mutation status of isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase (TERT) promoter, which are crucial for glioma prognostication and therapeutic decision-making, via sub-regional radiomics analysis based on multiparametric magnetic resonance imaging (MRI).

MATERIALS AND METHODS

A retrospective study was conducted on 401 participants with adult-type diffuse gliomas. Employing the K-means algorithm, tumours were clustered into two to four subregions. Sub-regional radiomics features were extracted and selected using the Mann-Whitney U-test, Pearson correlation analysis, and least absolute shrinkage and selection operator, forming the basis for predictive models. The performance of model combinations of different sub-regional features and classifiers (including logistic regression, support vector machines, K-nearest neighbour, light gradient boosting machine, and multilayer perceptron) was evaluated using an external test set.

RESULTS

The models demonstrated high predictive performance, with area under the receiver operating characteristic curve (AUC) values ranging from 0.918 to 0.994 in the training set for IDH mutation prediction and from 0.758 to 0.939 for TERT promoter mutation prediction. In the external test sets, the two-cluster radiomics features and the logistic regression model yielded the highest prediction for IDH mutation, resulting in an AUC of 0.905. Additionally, the most effective predictive performance with an AUC of 0.803 was achieved using the four-cluster radiomics features and the support vector machine model, specifically for TERT promoter mutation prediction.

CONCLUSION

The present study underscores the potential of sub-regional radiomics analysis in predicting IDH and TERT promoter mutations in glioma patients. These models have the capacity to refine preoperative glioma diagnosis and contribute to personalised therapeutic interventions for patients.

Ultra-stable hollow nanotube conjugated microporous polymer incorporating fluorenyl moieties for Co-capture of PM and CO2

Conjugated microporous polymers have a highly delocalized π-π conjugated porous skeleton connected by covalent bonds, which can combine their excellent stability with high adsorption, in order to be applied to the study of co-capture of harmful particulate matter (PM) and carbon dioxide (CO2) under high temperature and high humidity conditions. In this paper, fluorene-based coupled conjugated microporous polymers (D-CMPs) with functionalized hollow nanotubes and abundant microporous structures were proposed. Through mechanism exploration and molecular electrostatic potential (MESP) calculation, the capture efficiency, adsorption capacity and selectivity of PM and CO2 in the waste gas stream of carbon-based combustion were analyzed. The results indicate that D-CMPs, with their rigid carbon-based π-conjugated framework, exhibit excellent tolerance under prolonged high-humidity conditions, with a capture efficiency exceeding 99.87% for PM0.3 and exceeding 99.99% for PM2.5. Meanwhile, based on its chemical/thermal stability, it can realize the recycling of adsorption-regeneration. On this basis, the "slip effect" induced by the open three-dimensional hierarchical porous structure of D-CMPs significantly enhances airflow dispersion and improves gas throughput (with a minimal permeation resistance of only 15 Pa). At a pressure of 1 bar and a temperature of 273.15 K, D-CMP-2 exhibited a CO2 adsorption capacity of up to 2.69 mmol g-1. The fitting results of three isothermal adsorption models demonstrate that D-CMPs exhibit an outstanding equilibrium selectivity towards CO2. Therefore, prior to the widespread adoption of low-carbon and clean energy technologies, porous solid materials exhibiting excellent structural stability, equilibrium selectivity, environmental tolerance, and high adsorption capacity emerge as optimal candidates for the treatment of industrial waste gases.

Post-ERCP cholecystitis: Incidence, characteristics, and outcomes from a prospective multicenter biliary endoscopy registry

BACKGROUND AND AIMS

The incidence, risk factors, and outcomes of post-ERCP cholecystitis are poorly described. We aimed to describe cases of post-ERCP cholecystitis from a prospective multicenter registry with protocolized 30-day follow-up.

METHODS

Patient- and procedure-related data from 7 centers were obtained. The primary outcome was post-ERCP cholecystitis, defined according to a Delphi-based criteria and causal attribution system. Risk factors and outcomes were described for all cases.

RESULTS

Seventeen cases of post-ERCP cholecystitis were identified among 4428 patients with gallbladders undergoing ERCP between 2018 and 2023 (incidence, 0.38%; 95% confidence interval, 0.20-0.57). In ERCPs with covered metal stenting, 7 of 467 resulted in cholecystitis (incidence, 1.50%; 95% confidence interval, 0.40-2.60). Patients had symptoms at a median of 5 days (interquartile range, 5) after ERCP. Management strategies included cholecystectomy, percutaneous cholecystostomy, and endoscopic stent removal/exchange.

CONCLUSIONS

Estimates of post-ERCP cholecystitis incidence can inform discussions around procedural risk.

Modulating Th1/Th2 drift in asthma-related immune inflammation by enhancing bone mesenchymal stem cell homing through targeted inhibition of the Notch1/Jagged1 signaling pathway

Asthma, a disease intricately linked to immune inflammation, is significantly influenced by the immune regulatory effect of bone mesenchymal stem cells (BMSCs). This study aims to investigate changes in the homing of BMSCs in bronchial asthma, focusing on the Notch homolog (Notch)1/Jagged1 signaling pathway's role in regulating T helper 1(Th1)/T helper 2(Th2) drift. Additionally, we further explore the effects and mechanisms of homologous BMSCs implantation in asthma-related immune inflammation. Following intervention with BMSCs, a significant improvement in the pathology of rats with asthma was observed. Simultaneously, a reduction in the expression of inflammatory cells and inflammatory cytokines, including tumor necrosis factor-α (TNF-α), interleukin(IL)-4, and IL-13 was observed in bronchoalveolar lavage fluid (BALF). Furthermore, there was an increase in the expression of Th1 cytokine Interferon-γ（IFN-γ）and the transcription factor T-box expressed in T cell (T-bet), while the expression of Th2 cytokine IL-13 and transcription factor GATA binding protein (GATA)-3 decreased in lung tissue. This indicates that the Th1/Th2 drift leans towards Th1, which a crucial in ameliorating asthma inflammation. Importantly, inhibition of the Notch1 signaling pathway led to an increased expression of the Stromal cell-derived factor-1(SDF-1)/C-X-C motif chemokine receptor (CXCR)4 chemokine axis. Consequently, the homing ability of bone marrow mesenchymal stem cells to asthma-affected lung tissue was significantly enhanced. BMSCs demonstrated heightened efficacy in regulating the cytokine/chemokine network and Th1/Th2 balance, thereby restoring a stable state during the immune response process in asthma. In conclusion, inhibiting the Notch signaling pathway enhances the expression of the SDF-1 and CXCR4 chemokine axis, facilitating the migration of allogeneic BMSCs to injured lung tissues. This, in turn, promotes immune regulation and improves the Th1/Th2 imbalance, thereby enhancing the therapeutic effect on asthmatic airway inflammation.

Specific fractionation of ginsenosides based on activated carbon fibers and online fast screening of ginseng extract by mass spectrometry

Ginseng is beneficial in the prevention of many diseases and provides benefits for proper growth and development owing to the presence of various useful bioactive substances of diverse chemical heterogeneity (e.g., triterpenoid saponins, polysaccharides, volatile oils, and amino acids). As a result, understanding the therapeutic advantages of ginseng requires an in-depth compositional evaluation employing a simple and rapid analytical technique. In this work, three types of surface-activated carbon fibers (ACFs) were prepared by gas-phase oxidation, strong acid treatment, and Plasma treatment to obtain CO2-ACFs, acidified-ACFs, and plasma-ACFs, respectively. Three prepared ACFs were compared in terms of their physicochemical characterization (i.e., surface roughness and functional groups). A separation system was built using a column with modified ACFs, followed by mass spectrometry detection to investigate and determine substances of different polarities. Among the three columns, CO2-ACFs showed the optimum separation effect. 13 strong polar compounds (12 amino acids and1 oligosaccharide) and 15 lesser polar compounds (ginsenosides) were separated and identified successfully within 4 min in the ginseng sample. The data obtained by CO2-ACFs-TOF-MS/MS and UHPLC-TOF-MS/MS were compared. Our approach was found to be faster (4 min vs. 36 min) and greener, requiring much less solvent (1 mL vs. 10.8 mL), and power (0.06 vs. 0.6 kWh). The developed methodology can provide a faster, eco-friendly, and more reliable tool for the high-throughput screening of complex natural matrices and the simultaneous evaluation of several compounds in diverse samples.

UNVEILING THE PROTECTIVE MECHANISMS OF PUERARIN AGAINST ACUTE LUNG INJURY: A COMPREHENSIVE EXPLORATION OF THE ROLES AND MECHANISMS OF MST1/ERS SIGNALING

OBJECTIVES

Puerarin, the principal active constituent extracted from Pueraria, is believed to confer protection against sepsis-induced lung injury. The study aimed to elucidate the role and mechanism of Mst1/ERS in puerarin-mediated protection against acute lung injury (ALI).

METHODS

Monolayer vascular endothelial cell permeability was assessed by gauging the paracellular flow of FITC-dextran 40,000 (FD40). ELISA was employed for the quantification of inflammatory cytokines. Identification of target proteins was conducted through Western blotting. Histological alterations and apoptosis were scrutinized using H&E staining and TUNEL staining, respectively. The ultrastructure of the endoplasmic reticulum was observed via transmission electron microscopy.

RESULTS

Puerarin significantly protected mice from LPS-induced ALI, reducing lung interstitial width, neutrophil and lymphocyte infiltration, pulmonary interstitial and alveolar edema, and lung apoptosis. Puerarin treatment also markedly attenuated levels of TNF-α and IL-1β in both alveolar lavage fluid and serum. Furthermore, puerarin significantly attenuated LPS-induced increases in Mst1, GRP78, CHOP, and Caspase12 protein expression and blunted LPS-induced decrease in ZO-1 protein expression in lung tissues. Puerarin obviously reduced endoplasmic reticulum expansion and vesiculation. Similarly, puerarin significantly mitigated the LPS-induced reduction in HUVEC cell viability and ZO-1 expression. Puerarin also attenuated LPS-induced increase in apoptosis, TNF-α and IL-1β, FD40 flux, and Mst1, GRP78, CHOP, and Caspase12 expression in HUVEC cells. Nevertheless, the inhibitory impact of puerarin on vascular endothelial cell injury, lung injury, and endoplasmic reticulum stress (ERS) was diminished by Mst1 overexpression.

CONCLUSION

These findings demonstrated that the Mst1/ERS signaling pathway played a pivotal role in the development of LPS-induced vascular endothelial cell dysfunction and ALI. Puerarin exhibited the ability to attenuate LPS-induced vascular endothelial cell dysfunction and ALI by inhibiting the Mst1/ERS signaling pathway.

MiR-29a-3p mediates phosphatase and tensin homolog and inhibits osteoarthritis progression

Despite substantial progress in clinical trials of osteoarthritis (OA) gene therapy, the prevalence of OA is still on the rise. MiRNAs have a potential biomarker and therapeutic target for OA. OA cartilage and chondrosarcoma cells were studied to determine the role of miR-29a-3p and PTEN. OA cartilage and human chondrosarcoma cells (SW1353) were obtained. miR-29a-3p and PTEN signature expression was determined by RT-qPCR. The binding relationship between miR-29a-3p and PTEN was investigated by dual-luciferase reporter gene and western blot assay. TUNEL, immunohistochemistry, CCK-8, and flow cytometry were utilized to determine the proliferation and apoptosis of SW1353 cells. This study indicated downregulation of miR-29a-3p expression and upregulation of PTEN expression in human OA primary chondrocytes or OA tissue samples, compared with the normal cartilage cells or tissues. PTEN expression was negatively correlated with miR-29a-3p expression, and miR-29a-3p targeted PTEN mechanistically. miR-29a-3p reduced SW1353 cell activity and proliferation and promoted cell apoptosis. However, the aforementioned effects could be reversed by downregulating PTEN. miR-29a-3p can stimulate chondrocyte proliferation and inhibit apoptosis by inhibiting PTEN expression.

Electrochemical route outperforms chemical struvite precipitation in mitigating heavy metal contamination

Electrochemically mediated struvite precipitation (EMSP) offers a robust, chemical-free process towards phosphate and ammonium reclamation from nutrients-rich wastewater, i.e., swine wastewater. However, given the coexistence of heavy metal, struvite recovered from wastewater may suffer from heavy metal contamination. Here, we systematically investigated the fate of Cu2+, as a representative heavy metal, in the EMSP process and compared it with the chemical struvite precipitation (CSP) system. The results showed that Cu2+ was 100% transferred from solution to solid phase as a mixture of copper and struvite under pHi 9.5 with 2-20 mg/L Cu2+ in the CSP system, and varying pH would affect struvite production. In the EMSP system, the formation of struvite was not affected by bulk pH, and struvite was much less polluted by co-removed Cu2+ (24.4%) at pHi 7.5, which means we recovered a cleaner and safer product. Specifically, struvite mainly accumulates on the front side of the cathode. In contrast, the fascinating thing is that Cu2+ is ultimately deposited primarily to the back side of the cathode in the form of copper (hydro)oxides due to the distinct thickness of the local high pH layer on the two sides of the cathode. In turn, struvite and Cu (hydro)oxides can be harvested separately from the front and back sides of the cathode, respectively, facilitating the subsequent recycling of heavy metals and struvite. The contrasting fate of Cu2+ in the two systems highlights the merits of EMSP over conventional CSP in mitigating heavy metal pollution on recovered products, promoting the development of EMSP technology towards a cleaner recovery of struvite from waste streams.

Deformable lung 4DCT image registration via landmark-driven cycle network

BACKGROUND

An automated, accurate, and efficient lung four-dimensional computed tomography (4DCT) image registration method is clinically important to quantify respiratory motion for optimal motion management.

PURPOSE

The purpose of this work is to develop a weakly supervised deep learning method for 4DCT lung deformable image registration (DIR).

METHODS

The landmark-driven cycle network is proposed as a deep learning platform that performs DIR of individual phase datasets in a simulation 4DCT. This proposed network comprises a generator and a discriminator. The generator accepts moving and target CTs as input and outputs the deformation vector fields (DVFs) to match the two CTs. It is optimized during both forward and backward paths to enhance the bi-directionality of DVF generation. Further, the landmarks are used to weakly supervise the generator network. Landmark-driven loss is used to guide the generator's training. The discriminator then judges the realism of the deformed CT to provide extra DVF regularization.

RESULTS

We performed four-fold cross-validation on 10 4DCT datasets from the public DIR-Lab dataset and a hold-out test on our clinic dataset, which included 50 4DCT datasets. The DIR-Lab dataset was used to evaluate the performance of the proposed method against other methods in the literature by calculating the DIR-Lab Target Registration Error (TRE). The proposed method outperformed other deep learning-based methods on the DIR-Lab datasets in terms of TRE. Bi-directional and landmark-driven loss were shown to be effective for obtaining high registration accuracy. The mean and standard deviation of TRE for the DIR-Lab datasets was 1.20 ± 0.72 mm and the mean absolute error (MAE) and structural similarity index (SSIM) for our datasets were 32.1 ± 11.6 HU and 0.979 ± 0.011, respectively.

CONCLUSION

The landmark-driven cycle network has been validated and tested for automatic deformable image registration of patients' lung 4DCTs with results comparable to or better than competing methods.

Exogenous neuritin restores auditory following cochlear spiral ganglion neuron denervation of gerbils

Spiral ganglion neurons (SGNs) transmit sound signals received by hair cells to the auditory center to produce hearing. The quantity and function are important for maintaining normal hearing function. Limited by the regenerative capacity, SGNs are unable to regenerate spontaneously after injury. Various neurotrophic factors play an important role in the regeneration process. Neuritin is a neurite growth factor that plays an important role in neural plasticity and nerve injury repair. In this study, we used bioinformatics analysis to show that neuritin was negatively correlated with cochlear damage. Then, we aimed to establish a cochlear spiral ganglion-specific sensorineural deafness model in gerbils using ouabain and determine the effects of exogenous neuritin protein in protecting damaged cochlear SGNs and repairing damaged auditory nerve function. The provides a new research strategy and scientific basis for the prevention and treatment of sensorineural deafness caused by the loss of SGNs. We were discovered that neuritin is expressed throughout the development of the gerbil cochlea, primarily in the SGNs and Corti regions. The expression of neuritin was negatively correlated with the sensorineural deafness induced by ouabain. In vitro and in vivo revealed that neuritin significantly maintained the number and arrangement of SGNs and nerve fibers in the damaged cochlea and effectively protected the high-frequency listening function of gerbils.

Effects of microbial deodorizer on pig feces fermentation and the underlying deodorizing mechanism

Microbial deodorization is a novel strategy for reducing odor in livestock and poultry feces. Herein, 12 strains of ammonia (NH3) and 15 hydrogen sulfide (H2S) removing bacteria were obtained with a removal efficiency of 65.20-79.80% and 34.90-79.70%, respectively. A novel bacteria deodorant named MIX (Bacillus zhangzhouensis, Bacillus altitudinis, and Acinetobacter pittii at a ratio of 1:1:2) were obtained. MIX can shorten the temperature rising stage by 2 days and prolong the thermophilic stage by 4 days. The ability of MIX to remove NH3, H2S, and volatile fatty acids (VFAs) and the underlying removal mechanism were analyzed during pig feces fermentation. MIX can significantly reduce the concentrations of NH3 and H2S by 41.82% and 66.35% and increase the concentrations of NO3--N and SO42- by 7.80% and 8.83% (P < 0.05), respectively, on the 25th day. Moreover, the concentrations of acetic, propionate, iso-valerate, and valerate were significantly reduced. The dominant bacteria communities at the phylum level were Firmicutes, Proteobacteria, Bacteroidetes, and Spirochaetes. B. zhangzhouensis and B. altitudinis could convert NH4+-N to NO3--N, and A. pittii could transfer H2S to SO42-. This study revealed that bacteria deodorant can reduce the concentrations of NH3, H2S, and VFAs in pig feces and increase those of NH4+, NO3-, and SO42- and has excellent potential in deodorizing livestock and poultry feces composting.

Spinal infection caused by Aspergillus flavus in a diabetic: a case report and literature review

Spinal infections, notably those induced by Aspergillus flavus (A. flavus), represent a complex and uncommon clinical challenge. In individuals with diabetes mellitus, the risk is exacerbated due to a compromised immune response and a heightened vulnerability to non-standard pathogens. This case report chronicles the intricate diagnostic and treatment journey of a 59-year-old diabetic patient grappling with a spinal infection attributed to A. flavus. The diagnosis was delayed due to non-specific symptoms and unclear radiological signs. The administration of voriconazole, a targeted antifungal treatment, resulted in a significant clinical and radiological improvement, underscoring its effectiveness in treating such unusual fungal spinal infections; meanwhile, we found that terbinafine hydrochloride also has a similar effect in treating fungal spinal infections. This case underscores the importance of considering fungal causes in spinal infections among diabetic patients and highlights prompt diagnosis and individualized targeted antifungal therapy.

Machine-learning-based optical spectrum feature analysis for DoS attack detection in IP over optical networks

In this paper, we introduce a novel approach for detecting Denial of Service (DoS) attacks in software-defined IP over optical networks, leveraging machine learning to analyze optical spectrum features. This method employs machine learning to automatically process optical spectrum data, which is indicative of network security status, thereby identifying potential DoS attacks. To validate its effectiveness, we conducted both numerical simulations and experimental trials to collect relevant optical spectrum datasets. We then assessed the performance of three machine learning algorithms XGBoost, LightGBM, and the BP neural network in detecting DoS attacks. Our findings show that all three algorithms demonstrate a detection accuracy exceeding 97%, with the BP neural network achieving the highest accuracy rates of 99.55% and 99.74% in simulations and experiments, respectively. This research not only offers a new avenue for DoS attack detection but also enhances early detection capabilities in the underlying optical network through optical spectrum data analysis.

Percutaneous kyphoplasty combined with pediculoplasty for the surgical treatment of osteoporotic thoracolumbar burst fractures

OBJECTIVE

This study introduces a minimally invasive technique for efficient three-column reconstruction, augmentation, and stabilization of osteoporotic thoracolumbar burst fractures (OTLBFs).

METHODS

Sixty-eight patients with OTLBFs and no neurological deficits were included from July 2019 to September 2020. The patients were divided into two groups: the simple percutaneous kyphoplasty (PKP) group (n = 32) and the percutaneous kyphoplasty combined with pediculoplasty (PKCPP) group (n = 36). The clinical and radiological outcomes were assessed during a minimum 1-year follow-up period. Clinical outcomes were assessed via the visual analog scale (VAS) and modified MacNab grading criteria. The radiological outcomes included the Cobb angle (CA), anterior wall height (AWH), and posterior wall height (PWH). The surgery duration, postoperative analgesic dosage, length of hospital stay, and complications were recorded.

RESULTS

Surgery duration was not significantly different between the two groups (P > 0.05). The PKCPP group had a lower analgesic dosage and shorter hospital stay (P < 0.05). Postoperatively, the PKCPP group exhibited better VAS scores and modified MacNab scale scores (P < 0.05), but the differences at the last follow-up assessment were not significant (P > 0.05). Postoperative CA, AWH, and PWH correction were not significantly different on the first postoperative day (P > 0.05). However, the PKCPP group had significantly less CA and PWH loss of correction at the last follow-up visit (P < 0.05). The PKCPP group had significantly fewer complications (P < 0.05).

CONCLUSIONS

The PKCPP technique complements simple PKP for OTLBFs. It quickly relieves pain, maintains the vertebral body height and Cobb angle, ensures cement stabilization, and offers more stable three-column support.

DNA methylation-mediated repression of microRNA-410 promotes the growth of human glioma cells and triggers cell apoptosis through its interaction with STAT3

This study's purpose was to confirm the observed underexpression of miRNA-410 in glioma tissues and several glioma cells by Quantitative RT-PCR. Our findings suggest that epigenetic alterations occurring at the promoter region of miR-410 may be responsible for the reduced expression of miR-410 in glioma. The occurrence of DNA methylation in the miR-410 promoter was verified to be more prevalent through glioma tissues contrasted to adjacent non-tumor brain tissues through the utilization of methylation-specific PCR and CpG bisulfite sequencing sites in the miR-410 promoter region. Accordantly, miR-410 expression in glioma cell lines was observed to be significantly lesser in comparison to that of the human fetal glial cell line. In addition, it was demonstrated through gain- and loss-of-function investigations that miR-410 exerts significant regulation over cell growth, cell cycle development, and glioma cell apoptosis. The findings of the Luciferase reporter assay and western blot analysis indicate that miR-410 has a direct effect on the 3'-UTR of signal transducer and activator of transcription 3 (STAT3), thereby inhibiting its expression within glioma cells. Besides, our clinical investigation indicates a negative association between miR-410 expression and STAT3 within the glioma tissues of humans. In aggregate, the data provided in this investigation indicates that miR-410 is subjected to underexpression via DNA methylation. Furthermore, it has been observed to perform its function as a tumor suppressor in glioma cells through direct targeting of STAT3. The previously mentioned results could potentially have significant implications for the advancement of a new therapeutic approach for treating glioma.

Endovascular Therapy for Basilar Artery Occlusion in Sudden Onset to Maximal Deficit Ischemic Events

BACKGROUND

The presence of sudden onset to maximal deficit (SOTMD) in patients with acute basilar artery occlusion often results in more severe outcomes. However, the effect of endovascular therapy on SOTMD and whether the outcome is affected by onset-to-puncture time remain unclear.

METHODS AND RESULTS

This retrospective analysis was conducted using data from the prospective BASILAR (Endovascular Treatment for Acute Basilar Artery Occlusion Study Registry). Consecutive patients with basilar artery occlusion receiving endovascular therapy were dichotomized into SOTMD and non-SOTMD cohorts. The primary outcomes included a favorable outcome (modified Rankin scale 0-3), recanalization, and mortality at 90 days. The outcomes of patients with SOTMD were analyzed using multivariable logistic regression. In the multivariate analysis, a favorable outcome was similar between the two cohorts (odds ratio [OR], 0.88 [95% CI, 0.58-1.34]; P=0.5), although the mortality of patients with SOTMD was higher than that of patients with non-SOTMD (OR, 1.67 [95% CI, 1.14-2.44]; P=0.008). The probability of mortality increased from 40.0% at 1 hour to 70.0% at 6 hours in the SOTMD cohort, and favorable outcomes of patients with non-SOTMD declined from 38.0% at 1 hour to 18.0% at 8 hours.

CONCLUSIONS

No significant difference was observed in favorable outcomes between the SOTMD and non-SOTMD groups, although mortality was higher in the SOTMD cohort. The patients with SOTMD had a stronger time dependence for endovascular therapy in terms of mortality, while the time dependency regarding favorable outcome in the NSOTMD group was even higher.

REGISTRATION

URL: https://www.chictr.org.cn; Unique identifier: ChiCTR1800014759.

Three-dimensional analysis of mandibular morphology asymmetry and temporomandibular joint position in patients with unilateral Brodie bite

OBJECTIVE

Previous studies have shown unilateral posterior crossbite is associated with mandibular asymmetry in morphology and position. However, it remains unclear whether unilateral Brodie bite plays a similar role in mandibular development. Therefore, this study aims to investigate the morphological and positional symmetry of mandibles in patients with unilateral Brodie bite by three-dimensional anaylsis.

METHODS

Fourteen patients with unilateral Brodie bite (mean age 18.43 ± 4.24 years) and fourteen sex- and age-matched patients with normal occlusion (mean age 18.07 ± 5.48 years) underwent cone-beam computed tomography (CBCT) scans. 3D surface mesh models of their mandibles were established using Mimics Research 19.0. The surface matching percentage was compared between the original and mirrored mandible by Geomagic Control X software. Furthermore, the dimension and position of the temporomandibular joint (TMJ) were determined for both groups using InVivoDental 5.0.

RESULTS

For surface-to-surface deviation analysis, the percentage of mismatch in patients with unilateral Brodie bite was significantly higher than the control group at ±0.50 mm, ±0.75 mm, and ±1.00 mm tolerance (P < .001). In patients with unilateral Brodie syndrome, the condyles on the scissors-bite side showed a significantly more anterior position (P = .03), greater medial inclination (P < .01), and larger posterior TMJ space (P = .01) than the non-scissors-bite side.

CONCLUSION

Patients with unilateral Brodie bite exhibit a more asymmetrical mandibular morphology, with a greater anterior condylar position and posterior joint space on the scissors-bite side, indicating that early diagnosis and treatment may be necessary for patients with unilateral Brodie bite.

Comprehensive analysis of aflatoxin B1 biosynthesis in Aspergillus flavus via transcriptome-wide m6A methylome response to cycloleucine

Aspergillus flavus and its toxic aflatoxins secondary metabolites contaminate food and grains, posing a severe threat to human health and leading to liver cancer. Here, we demonstrated that cycloleucine blocked aflatoxin B1 synthesis by inhibiting N6-methyladenosine (m6A) methylation modification of messenger RNA (mRNA). m6A Methylation Immunoprecipitation Sequencing (m6A MeRIP-Seq)-based comprehensive transcriptome-wide m6A profiling identified 102 differentially expressed genes that underwent m6A modification, of which 22 hypermethylated genes were downregulated and 49 hypomethylated genes were upregulated, suggesting a negative correlation between m6A methylation and gene expression. Notably, cycloleucine inhibited aflatoxin B1 production via multiple targets. The m6A sites of several key genes involved in the aflatoxin B1 biosynthesis pathway were significantly enriched in the coding sequence and around the stop codon, resulting in their downregulation. Furthermore, m6A methylation on genes related to the aflatoxin B1 biosynthesis pathway led to reduced mRNA stability. Cycloleucine inhibition of aflatoxin B1 production highlights its potential as an agent for removing mycotoxins in environmental pollution. ENVIRONMENTAL IMPLICATION: Aflatoxins, highly carcinogenic secondary metabolites produced by Aspergillus flavus, frequently contaminate crops such as peanut, corn, wheat and sesame leading to irreversible loss in the quality and yield of agricultural products and posing serious threats to food safety. Aflatoxins has also been linked to developmental delays and liver cancer in humans. In our study, 'monitoring aflatoxin concentrations and its bioaccumulation in organisms' has been conducted. The results demonstrated that aflatoxin production in A. flavus was completely blocked after cycloleucine treatment. Additionally, we demonstrated that inhibition of aflatoxin was linked to N6-methyladenosine methylation of multiple genes in aflatoxin biosynthesis pathway.

DACH1 attenuated PA-induced renal tubular injury through TLR4/MyD88/NF-κB and TGF-β/Smad signalling pathway

BACKGROUND

Palmitic acid (PA), the major saturated fatty acid in the blood, often induces the initiation and progression of diabetic kidney disease (DKD). However, the underlying mechanism remains unclear. DACH1 is an important regulator of kidney functions. Herein, we investigated the roles of DACH1 in PA-induced kidney injury.

METHODS

Clinical data from the NHANES database were subjected to analyse the association between serum PA (sPA), blood glucose and kidney function. Molecular docking of PA was performed with DACH1. Immunohistochemistry, cell viability, annexin V/7-AAD double staining, TUNEL assay, immunofluorescent staining, autophagic flux analysis, qRT-PCR and western blot were performed.

RESULTS

Clinical data confirmed that sPA was increased significantly in the pathoglycemia individuals compared with controls and correlated negatively with renal function. Our findings suggested that PA could dock with DACH1. DACH1 enhances cell viability by inhibiting apoptosis and attenuating autophagy blockage induced by PA. Furthermore, the results demonstrated that DACH1 ameliorated inflammation and fibrosis through TLR4/MyD88/NF-κB and TGF-β/Smad signalling pathway in PA-treated renal tubular epithelial cell line (HK-2).

CONCLUSIONS

This study proved that sPA presents a risk factor for kidney injuries and DACH1 might serve as a protective target against renal function deterioration in diabetic patients.

Novel Life Prediction Method of PMMA for Cultural Relics Protection Based on the BP Neural Network

Poly(methyl methacrylate) (PMMA) is widely used in the preservation and exhibition of cultural relics in museums. Accurately predicting its service life can help avoid many negative effects caused by PMMA aging. To study the change in the yellowing index of PMMA after aging in a UV light environment, an aging experiment was conducted. A prediction model for the service life of PMMA was established using nonlinear curve fitting and a back propagation (BP) neural network. By comparing the goodness of fit, simulation and modeling capabilities of the initial data, and the predictive ability for new data, it was found that the BP neural network prediction model outperformed the nonlinear curve fitting prediction model. In this study, the service life of newly produced PMMA samples was calculated as 7.83, 8.47, and 8.42 years, based on the yellowing index of retired PMMA as a benchmark and using the output data from the BP neural network prediction model. At this time, the performance and exhibition effect of the PMMA are poor, and the batch of PMMA needs to be updated.

Dynamic Risk Assessment of Voltage Violation in Distribution Networks with Distributed Generation

In response to the growing demand for economic and social development, there has been a significant increase in the integration of distributed generation (DG) into distribution networks. This paper proposes a dynamic risk assessment method for voltage violations in distribution networks with DG. Firstly, considering the characteristics of random variables such as load and DG, a probability density function estimation method based on boundary kernel density estimation is proposed. This method accurately models the probability of random variables under different time and external environmental conditions, such as wind speed and global horizontal radiation. Secondly, to address the issue of correlated DG in the same region, an independent transformation method based on the Rosenblatt inverse transform is proposed, which enhances the accuracy of probabilistic load flow. Thirdly, a voltage violation severity index based on the utility function is proposed. This index, in combination with probabilistic load flow results, facilitates the quantitative assessment of voltage violation risks. Finally, the accuracy of the proposed method is verified on the IEEE-33 system.

Lesion segmentation on 18F-fluciclovine PET/CT images using deep learning

Background and purpose

A novel radiotracer, 18F-fluciclovine (anti-3-18F-FACBC), has been demonstrated to be associated with significantly improved survival when it is used in PET/CT imaging to guide postprostatectomy salvage radiotherapy for prostate cancer. We aimed to investigate the feasibility of using a deep learning method to automatically detect and segment lesions on 18F-fluciclovine PET/CT images.

Materials and methods

We retrospectively identified 84 patients who are enrolled in Arm B of the Emory Molecular Prostate Imaging for Radiotherapy Enhancement (EMPIRE-1) trial. All 84 patients had prostate adenocarcinoma and underwent prostatectomy and 18F-fluciclovine PET/CT imaging with lesions identified and delineated by physicians. Three different neural networks with increasing levels of complexity (U-net, Cascaded U-net, and a cascaded detection segmentation network) were trained and tested on the 84 patients with a fivefold cross-validation strategy and a hold-out test, using manual contours as the ground truth. We also investigated using both PET and CT or using PET only as input to the neural network. Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD95), center-of-mass distance (CMD), and volume difference (VD) were used to quantify the quality of segmentation results against ground truth contours provided by physicians.

Results

All three deep learning methods were able to detect 144/155 lesions and 153/155 lesions successfully when PET+CT and PET only, respectively, served as input. Quantitative results demonstrated that the neural network with the best performance was able to segment lesions with an average DSC of 0.68 ± 0.15 and HD95 of 4 ± 2 mm. The center of mass of the segmented contours deviated from physician contours by approximately 2 mm on average, and the volume difference was less than 1 cc. The novel network proposed by us achieves the best performance compared to current networks. The addition of CT as input to the neural network contributed to more cases of failure (DSC = 0), and among those cases of DSC > 0, it was shown to produce no statistically significant difference with the use of only PET as input for our proposed method.

Conclusion

Quantitative results demonstrated the feasibility of the deep learning methods in automatically segmenting lesions on 18F-fluciclovine PET/CT images. This indicates the great potential of 18F-fluciclovine PET/CT combined with deep learning for providing a second check in identifying lesions as well as saving time and effort for physicians in contouring.

[Periodic dynamic observation and analysis of cellular and humoral immunity indexes of adults infected with Omicron BA.1]

Objective: To analyze the immunological characteristics and antibody changes of patients infected with the Omicron BA.1 and evaluate the possibility of secondary infection. Methods: A total of 104 patients infected with Omicron BA.1 in the Jinnan District of Tianjin from January 8 to February 2, 2022, were included in the study. The control group and case group were matched 1∶1 based on age, sex and vaccination status. Serum was collected from the case group and control group at 3, 6 and 9 months after infection. The serum levels of interleukin4 (IL-4), IL-5 and interferon-gamma (IFN-γ), as well as the positive rates of IgG, IgG1 and IgG2, were detected by ELISA. Results: The highest concentration of IFN-γ in the case group at 6 months after infection was 145.4 pg/ml, followed by a decrease in concentration. The concentrations of IL-4 and IL-5 began to decrease at 6 months after infection (all P<0.001). There was no significant difference in the IgG2 positive rate between the case group and the control group at 6 months after BA.1 infection. However, at 9 months, there was a significant decrease compared to the control group (P=0.003). The ratio of IFN-γ/IL4 at 3 months after infection in the case group was lower than that in the control group (P<0.001). There was no significant difference in the ratio between the case group and the control group at 9 months after infection. Conclusion: The cellular immune function has been impaired at 3 months after infection with BA.1, and the specific cellular immune and humoral immune functions decrease significantly after 6 months, and the risk of secondary infection increases.

Hippocampus substructure segmentation using morphological vision transformer learning

The hippocampus plays a crucial role in memory and cognition. Because of the associated toxicity from whole brain radiotherapy, more advanced treatment planning techniques prioritize hippocampal avoidance, which depends on an accurate segmentation of the small and complexly shaped hippocampus. To achieve accurate segmentation of the anterior and posterior regions of the hippocampus from T1 weighted (T1w) MR images, we developed a novel model, Hippo-Net, which uses a cascaded model strategy. The proposed model consists of two major parts: (1) a localization model is used to detect the volume-of-interest (VOI) of hippocampus. (2) An end-to-end morphological vision transformer network (Franchietal2020Pattern Recognit.102107246, Ranemetal2022 IEEE/CVF Conf. on Computer Vision and Pattern Recognition Workshops (CVPRW) pp 3710-3719) is used to perform substructures segmentation within the hippocampus VOI. The substructures include the anterior and posterior regions of the hippocampus, which are defined as the hippocampus proper and parts of the subiculum. The vision transformer incorporates the dominant features extracted from MR images, which are further improved by learning-based morphological operators. The integration of these morphological operators into the vision transformer increases the accuracy and ability to separate hippocampus structure into its two distinct substructures. A total of 260 T1w MRI datasets from medical segmentation decathlon dataset were used in this study. We conducted a five-fold cross-validation on the first 200 T1w MR images and then performed a hold-out test on the remaining 60 T1w MR images with the model trained on the first 200 images. In five-fold cross-validation, the Dice similarity coefficients were 0.900 ± 0.029 and 0.886 ± 0.031 for the hippocampus proper and parts of the subiculum, respectively. The mean surface distances (MSDs) were 0.426 ± 0.115 mm and 0.401 ± 0.100 mm for the hippocampus proper and parts of the subiculum, respectively. The proposed method showed great promise in automatically delineating hippocampus substructures on T1w MR images. It may facilitate the current clinical workflow and reduce the physicians' effort.

Denoising magnetic resonance spectroscopy (MRS) data using stacked autoencoder for improving signal-to-noise ratio and speed of MRS

BACKGROUND

While magnetic resonance imaging (MRI) provides high resolution anatomical images with sharp soft tissue contrast, magnetic resonance spectroscopy (MRS) enables non-invasive detection and measurement of biochemicals and metabolites. However, MRS has low signal-to-noise ratio (SNR) when concentrations of metabolites are in the range of millimolar. Standard approach of using a high number of signal averaging (NSA) to achieve sufficient SNR comes at the cost of a long acquisition time.

PURPOSE

We propose to use deep-learning approaches to denoise MRS data without increasing NSA. This method has potential to reduce the acquisition time as well as improve SNR and quality of spectra, which could enhance the diagnostic value and broaden the clinical applications of MRS.

METHODS

The study was conducted using data collected from the brain spectroscopy phantom and human subjects. We utilized a stack auto-encoder (SAE) network to train deep learning models for denoising low NSA data (NSA = 1, 2, 4, 8, and 16) randomly truncated from high SNR data collected with high NSA (NSA = 192), which were also used to obtain the ground truth. We applied both self-supervised and fully-supervised training approaches and compared their performance of denoising low NSA data based on improvement in SNR. To prevent overfitting, the SAE network was trained in a patch-based manner. We then tested the denoising methods on noise-containing data collected from the phantom and human subjects, including data from brain tumor patients. We evaluated their performance by comparing the SNR levels and mean squared errors (MSEs) calculated for the whole spectra against high SNR "ground truth", as well as the value of chemical shift of N-acetyl-aspartate (NAA) before and after denoising.

RESULTS

With the SAE model, the SNR of low NSA data (NSA = 1) obtained from the phantom increased by 28.5% and the MSE decreased by 42.9%. For low NSA data of the human parietal and temporal lobes, the SNR increased by 32.9% and the MSE decreased by 63.1%. In all cases, the chemical shift of NAA in the denoised spectra closely matched with the high SNR spectra without significant distortion to the spectra after denoising. Furthermore, the denoising performance of the SAE model was more effective in denoising spectra with higher noise levels.

CONCLUSIONS

The reported SAE denoising method is a model-free approach to enhance the SNR of MRS data collected with low NSA. With the denoising capability, it is possible to acquire MRS data with a few NSA, shortening the scan time while maintaining adequate spectroscopic information for detecting and quantifying the metabolites of interest. This approach has the potential to improve the efficiency and effectiveness of clinical MRS data acquisition by reducing the scan time and increasing the quality of spectroscopic data.

Single energy CT-based mass density and relative stopping power estimation for proton therapy using deep learning method

Background

The number of patients undergoing proton therapy has increased in recent years. Current treatment planning systems (TPS) calculate dose maps using three-dimensional (3D) maps of relative stopping power (RSP) and mass density. The patient-specific maps of RSP and mass density were obtained by translating the CT number (HU) acquired using single-energy computed tomography (SECT) with appropriate conversions and coefficients. The proton dose calculation uncertainty of this approach is 2.5%-3.5% plus 1 mm margin. SECT is the major clinical modality for proton therapy treatment planning. It would be intriguing to enhance proton dose calculation accuracy using a deep learning (DL) approach centered on SECT.

Objectives

The purpose of this work is to develop a deep learning method to generate mass density and relative stopping power (RSP) maps based on clinical single-energy CT (SECT) data for proton dose calculation in proton therapy treatment.

Methods

Artificial neural networks (ANN), fully convolutional neural networks (FCNN), and residual neural networks (ResNet) were used to learn the correlation between voxel-specific mass density, RSP, and SECT CT number (HU). A stoichiometric calibration method based on SECT data and an empirical model based on dual-energy CT (DECT) images were chosen as reference models to evaluate the performance of deep learning neural networks. SECT images of a CIRS 062M electron density phantom were used as the training dataset for deep learning models. CIRS anthropomorphic M701 and M702 phantoms were used to test the performance of deep learning models.

Results

For M701, the mean absolute percentage errors (MAPE) of the mass density map by FCNN are 0.39%, 0.92%, 0.68%, 0.92%, and 1.57% on the brain, spinal cord, soft tissue, bone, and lung, respectively, whereas with the SECT stoichiometric method, they are 0.99%, 2.34%, 1.87%, 2.90%, and 12.96%. For RSP maps, the MAPE of FCNN on M701 are 0.85%, 2.32%, 0.75%, 1.22%, and 1.25%, whereas with the SECT reference model, they are 0.95%, 2.61%, 2.08%, 7.74%, and 8.62%.

Conclusion

The results show that deep learning neural networks have the potential to generate accurate voxel-specific material property information, which can be used to improve the accuracy of proton dose calculation.

Advances in knowledge

Deep learning-based frameworks are proposed to estimate material mass density and RSP from SECT with improved accuracy compared with conventional methods.

Smart nanoparticles for cancer therapy

Smart nanoparticles, which can respond to biological cues or be guided by them, are emerging as a promising drug delivery platform for precise cancer treatment. The field of oncology, nanotechnology, and biomedicine has witnessed rapid progress, leading to innovative developments in smart nanoparticles for safer and more effective cancer therapy. In this review, we will highlight recent advancements in smart nanoparticles, including polymeric nanoparticles, dendrimers, micelles, liposomes, protein nanoparticles, cell membrane nanoparticles, mesoporous silica nanoparticles, gold nanoparticles, iron oxide nanoparticles, quantum dots, carbon nanotubes, black phosphorus, MOF nanoparticles, and others. We will focus on their classification, structures, synthesis, and intelligent features. These smart nanoparticles possess the ability to respond to various external and internal stimuli, such as enzymes, pH, temperature, optics, and magnetism, making them intelligent systems. Additionally, this review will explore the latest studies on tumor targeting by functionalizing the surfaces of smart nanoparticles with tumor-specific ligands like antibodies, peptides, transferrin, and folic acid. We will also summarize different types of drug delivery options, including small molecules, peptides, proteins, nucleic acids, and even living cells, for their potential use in cancer therapy. While the potential of smart nanoparticles is promising, we will also acknowledge the challenges and clinical prospects associated with their use. Finally, we will propose a blueprint that involves the use of artificial intelligence-powered nanoparticles in cancer treatment applications. By harnessing the potential of smart nanoparticles, this review aims to usher in a new era of precise and personalized cancer therapy, providing patients with individualized treatment options.

Flow-through electrochemical organophosphorus degradation and phosphorus recovery: The essential role of chlorine radical

Phosphorus scarcity and the deleterious ecological impact of the release of organophosphorus pesticides have emerged as critical global issues. Previous research has shown the ability of electrochemistry to induce the precipitation of calcium phosphate from phosphorus-laden wastewater to recover the phosphorus. The current study presents a flow-through electrochemical system consisting of a column-shaped electrochemical reactor, a tubular stainless-steel (SS) cathode, and a titanium suboxides (TiSO) anode. This system simultaneously oxidizes tetrakis (hydroxymethyl) phosphonium sulfate (THPS) and recycles phosphates. The influence of current density, flow rate, and initial calcium ions concentration were examined under continuous flow operation. To enhance the electrochemical reactor's performance, we elevated the current density from 5 to 30 mA cm-2, which caused the phosphorus recovery efficiency to increase from 37% to 72% within 120 min, accompanied by an enhancement of the THPS mineralization efficiency from 57% to 90%. These improvements were likely due to the higher yield of reactive species chloride species (Cl•) formed at the TiSO anode and the higher local pH at the cathode. By investigating the formation of Cl• at the TiSO anode, we found that THPS mineralization exceeded 75% in the presence of NaCl at a current density of 20 mA cm-2. The demonstrated performance of the flow-through electrochemical system should enable the utilization of anodic oxidation-cathodic precipitation for the recovery of phosphorus from organophosphorus-contaminated wastewater.

Interaction of PALE CRESS with PAP2/pTAC2 and PAP3/pTAC10 affects the accumulation of plastid-encoded RNA polymerase complexes in Arabidopsis

The transcription of photosynthesis genes in chloroplasts is largely mediated by the plastid-encoded RNA polymerase (PEP), which resembles prokaryotic-type RNA polymerases, but with plant-specific accessory subunits known as plastid transcriptionally active chromosome proteins (pTACs) or PEP-associated proteins (PAPs). However, whether additional factors are involved in the biogenesis of PEP complexes remains unknown. Here, we investigated the function of an essential gene, PALE CRESS (PAC), in the accumulation of PEP complexes in chloroplasts. We established that an Arabidopsis leaf variegation mutant, variegated 6-1 (var6-1), is a hypomorphic allele of PAC. Unexpectedly, we revealed that a fraction of VAR6/PAC is associated with thylakoid membranes, where it interacts with PEP complexes. The accumulation of PEP complexes is defective in both var6-1 and the null allele var6-2. Further protein interaction assays confirmed that VAR6/PAC interacts directly with the PAP2/pTAC2 and PAP3/pTAC10 subunits of PEP complexes. Moreover, we generated viable hypomorphic alleles of the essential gene PAP2/pTAC2, and revealed a genetic interaction between PAC and PAP2/pTAC2 in photosynthesis gene expression and PEP complex accumulation. Our findings establish that VAR6/PAC affects PEP complex accumulation through interactions with PAP2/pTAC2 and PAP3/pTAC10, and provide new insights into the accumulation of PEP and chloroplast development.

Metastasis of ovarian cancer to nasal skin and skin on the trunk: a rare case report

Cutaneous metastases of ovarian cancer are rare and often have poor prognosis. We report a case of a 62-year-old woman with recurrent low-grade serous ovarian cancer, who presented with lung, brain, and multiple skin (nasal and anterior chest wall) metastases approximately six months after the initial diagnosis. In this case, Nijmegen breakage syndrome carrier status caused by RAD50 heterozygous mutation and previous bevacizumab therapy could be the predisposing factor for cutaneous metastases. The patient was treated with local radiotherapy (nasal skin and brain, 30Gy/6f/1.2W) and three courses of chemotherapy with albumin-bound paclitaxel and carboplatin, resulting in drastic remission of the cutaneous metastases. Unfortunately, treatment interruption resulted in rapid tumor progression, followed by death. This case represents an interesting example of cutaneous metastasis of ovarian cancer with rare clinical manifestations, unique genetic mutations, and reasonable response to treatment. Chemoradiotherapy might be an appropriate option for cutaneous metastases of ovarian cancer. Nevertheless, we still hope to find out the best treatment strategy after collecting and reviewing more cases in the future.

Delta-Radiomics Guides Adaptive De-Intensification after Induction Chemotherapy in Locoregionally Advanced Nasopharyngeal Carcinoma in the IMRT Era

PURPOSE/OBJECTIVE(S)

In the setting of intensity-modulated radiotherapy (IMRT) and induction chemotherapy (IC), the benefits from concurrent chemotherapy remained controversial for locoregionally advanced nasopharyngeal carcinoma (LANPC). This study aimed to construct a delta-radiomics model for benefit prediction and patient selection for omitting concurrent chemotherapy.

MATERIALS/METHODS

Between December 2009 and December 2015, a total of 718 patients with LANPC treated with IC+IMRT or IC+concurrent chemoradiotherapy (CCRT) were retrospectively enrolled and randomly assigned to a training set (n = 503) and a validation set (n = 215). Radiomic features were extracted from magnetic resonance images of pre-IC and post-IC. Interclass correlation coefficients and Pearson correlation coefficients were calculated to select robust radiomic features. After univariate Cox analysis, a delta-radiomics signature was built using the LASSO-Cox regression. A nomogram incorporating the delta-radiomics signature and clinical prognostic factors was then developed and evaluated for calibration and discrimination. Risk stratification by the nomogram was evaluated by Kaplan-Meier methods. The primary outcome was overall survival (OS).

RESULTS

The delta-radiomics signature, which comprised 19 selected features, was independently associated with prognosis. It yielded an area under the receiver operating characteristic curve (AUC) of 0.77 (95% confidence interval [CI] 0.71 to 0.82) for the training set and 0.71 (95% CI 0.61 to 0.81) for the validation set. The nomogram composed of the delta-radiomic signature, age, T category, N category, pre-treatment Epstein-Barr virus DNA, and treatment showed great calibration and discrimination performance with an AUC of 0.80 (95% CI 0.75 to 0.85) for the training set and 0.75 (95% CI 0.64 to 0.85) for the validation set. Risk stratification by the nomogram excluding the treatment variable resulted in two risk groups with distinct OS. Significant better outcomes were observed in the high-risk patients with IC+CCRT compared to those with IC+IMRT (5-year OS: 73.8% vs. 61.4% in the training set and 85.8% vs. 65.6% in the validation set; all log-rank p < 0.05), while comparable outcomes between IC+CCRT and IC+IMRT were shown for the low-risk patients (95.8% vs. 95.8% in the training set and 92.2% vs. 88.3% in the validation set; all log-rank p > 0.05).

CONCLUSION

The delta-radiomics signature was identified as an independent indicator of LANPC. Integrating clinical predictors with the delta-radiomics signature, the radiomics-based nomogram could predict individual's survival outcomes and benefits from concurrent chemotherapy after IC for LANPC. Low-risk patients with LANPC determined by the nomogram may be potential candidates for omission of concurrent chemotherapy following IC in the IMRT era.

Rapid Unpaired CBCT-Based Synthetic CT for CBCT-Guided Adaptive Radiotherapy

PURPOSE/OBJECTIVE(S)

Quantitative cone beam CT (CBCT) is the foundation for image-guided radiation therapy, improving treatment setup, tumor delineation and dose calculation. However, CBCT images suffer from severe artifacts, limiting clinical utility. Deep learning can overcome these limitations, boosting radiographic and dosimetric quality critical for online adaptive radiotherapy (ART). We hypothesize adapted contrastive unpaired translation (CUT), a recent method for image-to-image translation of photographic images, can improve CBCT quality while reducing compute time, demonstrating utility for ART.

MATERIALS/METHODS

Same-day CBCT and quality assurance CT (QACT) images acquired from 79 patients receiving proton therapy for prostate cancer between 2019 and 2020 at a single institution were retrospectively collected. QACT images were acquired for quality assurance in accordance with institutional policy. Seventy-nine patients yielded 102 non-contrast CBCT-QACT image sets. Each QACT image was rigidly registered to the corresponding CBCT and resampled to 1 × 1 × 2 mm to establish uniform voxel size and spacing. CBCT images were randomly shuffled prior to input to the CUT model for unsupervised training and QACT-quality synthetic CT images were generated as outputs. We compared mean absolute error (MAE), structural similarity index measure (SSIM), and Fréchet inception distance (FID) against same-day QACT.

RESULTS

MAE, SSIM, and FID were compared for the CycleGAN and CUT data relative to input QACT and are reported as the mean across five-fold cross-validation ± standard error. CUT achieved superior performance in MAE (19.5 ± 3.9 HU vs. cycleGAN 47.1 ± 25.4) and FID (31.5 ± 6.6 vs cycleGAN 75.9 ± 41.3). MAE indicates pixel-level correspondence to QACT HU intensity values, making the synthetic outputs of CUT useful for dose calculations during ART. FID further demonstrates perceptual visual similarity. SSIM for CycleGAN (0.7 ± 0.2) and CUT (0.8 ± 0.0) were similar, indicating acceptable reproducibility of global structure. CUT was faster and lighter than CycleGAN. CycleGAN contained a total of 28,286,000 parameters; CUT contained 14,703,000, approximately half that of CycleGAN. As a result, CycleGAN computes on a single CT image slice over 0.33s while CUT requires just 0.18s.

CONCLUSION

The contrastive method investigated here was demonstrated to be faster and more accurate than CycleGAN, requiring fewer networks and parameters to achieve superior performance. We demonstrated anatomic boundary preservation and HU fidelity superior to cycleGAN while significantly reducing compute time. We plan to investigate the use of these synthetic CT images in automated segmentation prior to exploration of CUT in a prospective setting.

Initial Experience with the Commercial Electron FLASH Research Extension

PURPOSE/OBJECTIVE(S)

The purpose of this study was to introduce a new commercial electron FLASH system that has the potential to become widely available for FLASH researchers globally. In this study, we first present the initial acceptance and commissioning tests for the FLASH system, and second, we highlight preliminary FLASH effect results from our cell studies.

MATERIALS/METHODS

A linear accelerator was converted into a commercial research platform with the FLASH Research Extension, enabling the generation of a powerful 16 MeV electron FLASH beam. The dosimetric and stability tests were conducted using various dosimeters (i.e., radiochromic film, optically stimulated luminescent dosimeters (OSLDs), and a plane-parallel ionization chamber). To evaluate the FLASH effect, normal and cancer cell lines were FLASH irradiated using different pulse repetition frequencies (PRF) of 18 pulses/s and 180 pulses/s.

RESULTS

The electron FLASH mode was able to generate over 1 Gy per pulse at the isocenter and a dose rate of up to 690 Gy/s near the accessory mount of the Linac gantry head. The charge collected by the plane-parallel ionization chamber at the highest PRF (i.e., 180 pulses/s) showed a linear relationship with the delivered number of pulses (i.e., 1 to 99 pulses) with a coefficient of determination (R2) of 0.9996. The absorbed dose measured using radiochromic film and OSLDs agreed within 3%, on average, and followed an inverse square law as the source-to-axis distance (SAD) varied for which the R2 values were 0.9972 and 0.9955 for radiochromic film and OSLDs, respectively. The profile of the FLASH beam was symmetrical but was not as flat as the conventional 16 MeV electron beam due to the use of a thinner custom scattering foil to reduce the degradation of the ultra-high dose rate. The depth-dose curve beyond the build-up region for the FLASH beam was similar to the conventional 16 MeV electron beam for which the range at 50% the maximum dose (R50) agreed within 0.5 mm. The FLASH beam output remained consistent over a 4-month period with a variation of 2.5%, on average. The FLASH sparing effect was observed in vitro for healthy human pancreatic cells. Furthermore, we observed that the highest PRF beam (180 pulses/s) was more effective at destroying pancreatic cancerous cells while minimizing damage to healthy cells compared to the lowest PRF beam (18 pulses/s).

CONCLUSION

The novel commercial FLASH Research Extension system was dosimetrically characterized for pre-clinical FLASH research, and preliminary in vitro results demonstrated the FLASH effect. Given the prevalence of linear accelerators, this new commercial system has the potential to greatly increase the access to FLASH research.

Biomimetic-modified bioprosthetic heart valves with Cysteine-Alanine-Glycine peptide for anti-thrombotic, endothelialization and anti-calcification

In recent years, bioprosthetic heart valves (BHVs) prepared by cross-linking porcine or bovine pericardium with glutaraldehyde (Glut) have received widespread attention due to their excellent hemocompatibility and hydrodynamic properties. However, the failure of BHVs induced by thrombosis and difficulty in endothelialization still exists in clinical practice. Improving the biocompatibility and endothelialization potential of BHVs is conducive to promoting their anti-thrombosis properties and prolonging their service life. Herein, Cysteine-Alanine-Glycine (CAG) peptide was introduced into the biomimetic BHV materials modified by 2-methacryloyloxyethyl phosphorylcholine (MPC) to improve their anti-thrombosis and promoting-endothelialization performances. MPC can improve the anti-adsorption performance of BHV materials, as well as, CAG contributes to the adhesion and proliferation of endothelial cells on the surface of BHV materials. The results of experiments showed that the biomimetic modification strategy with MPC and CAG reduce the thrombosis of BHV materials and improve their endothelialization in vitro. More importantly, the calcification of BHV significantly reduced by inhibiting the expression of M1 macrophage-related factors (IL-6, iNOS) and promoting the expression of M2 macrophage-related factors (IL-10, CD206). We believe that the valve-modified strategy is expected to provide effective solutions to clinical valve problems.

Commissioning and Initial Validation of Commercial Treatment Planning System for the Electron FLASH Research Extension

PURPOSE/OBJECTIVE(S)

The aim of this study was to investigate the feasibility of commissioning the 16 MeV electron FLASH beam in a commercial treatment planning system (TPS) for pre-clinical research purposes. The delivery system consisted of a new commercial solution for which a linear accelerator was modified into a FLASH Research Extension platform. Additionally, preliminary radiation biology results were highlighted to showcase the future use of this system.

MATERIALS/METHODS

To commission a commercial electron Monte Carlo (MC) for dose calculation of a 16 MeV FLASH beam in the TPS, radiochromic film was used to measure the vendor-required beam data, e.g., profiles and percent depth dose (PDD) curves for cone sizes of 6 × 6 cm2, 10 × 10 cm2, and 15 × 15 cm2 as well as an in-air profile for a 40 × 40 cm2 open field (no cone). Once the electron MC beam model was generated, additional measurements were collected for validation and compared against the calculated dose from the TPS. A treatment planning comparison between the newly commissioned FLASH beam and the conventional electron beam was conducted. Specifically, the dose-volume histograms (DVHs) for target volumes and organs at risk were investigated for skin cancer cases previously treated with conventional electron beams. Lastly, the FLASH dose distribution predicted by the electron MC for an in vitro cell study setup was validated with radiochromic film measurements, and initial radiobiology tests were conducted using FLASH and conventional dose-rate electron beams.

RESULTS

The electron MC calculated dose for the 16 MeV electron FLASH beam agreed with measured PDDs within 1% for all field sizes. The beam profile characteristics, such as penumbra, shape, and full width at half maximum, demonstrated good agreement with less than 0.5 mm difference between the TPS and measurements. There were noticeable differences in the profiles of large fields between the FLASH and conventional dose-rate beam models due to the more forward-peaked FLASH beam. For treatment planning, Regarding DVH, the FLASH dose-rate plan provided comparable plan quality to the conventional dose-rate plan, achieving adequate coverage for the target volumes and sparing the healthy organs and tissues. The electron MC dose prediction for the FLASH beam was also found to be in good agreement with the film measurements of the in vitro cell study setup. Furthermore, the FLASH beam was observed to be more effective with a 20 % increase in killing pancreatic cancer cells compared to the conventional dose rate.

CONCLUSION

The study successfully incorporated the 16 MeV electron FLASH Research Extension into the commercial TPS using electron Monte Carlo for dose calculation. This will be valuable for pre-clinical cell and animal studies. This research also enables FLASH treatment planning studies, a key component for the future implementation of FLASH into clinical care. Further research is necessary to incorporate the radiation biology effect of FLASH into the treatment planning system.

Rapid unpaired CBCT-based synthetic CT for CBCT-guided adaptive radiotherapy

In this work, we demonstrate a method for rapid synthesis of high-quality CT images from unpaired, low-quality CBCT images, permitting CBCT-based adaptive radiotherapy. We adapt contrastive unpaired translation (CUT) to be used with medical images and evaluate the results on an institutional pelvic CT dataset. We compare the method against cycleGAN using mean absolute error, structural similarity index, root mean squared error, and Frèchet Inception Distance and show that CUT significantly outperforms cycleGAN while requiring less time and fewer resources. The investigated method improves the feasibility of online adaptive radiotherapy over the present state-of-the-art.

SNTB1 regulates colorectal cancer cell proliferation and metastasis through YAP1 and the WNT/β-catenin pathway

Colorectal cancer is a common type of digestive tract cancer with a significant morbidity and death rate across the world, partially attributing to the metastasis-associated problems. In this study, integrative bioinformatics analyses were performed to identify genes that might contribute to colorectal cancer metastasis, and 293 genes were dramatically increased and 369 genes were decreased within colon cancer samples. Among up-regulated genes, top five genes correlated with colorectal cancer patient's prognosis were verified for expression in clinical samples and syntrophin beta 1 (SNTB1) was the most up-regulated. In vitro, SNTB1 knockdown suppresses the malignant behaviors of colorectal cancer cells, including cell viability, colony formation capacity, as well as the abilities to migrate and invade. Furthermore, SNTB1 knockdown decreased the levels of Wnt1, C-Jun, C-Myc, TCF7, and cyclin D1, and inhibited EMT in both cell lines. In vivo, SNTB1 knockdown inhibited tumor growth and metastasis in nude mice models. SNTB1 positively regulated Yes1 associated transcriptional regulator (YAP1) expression; YAP1 partially reversed the effects of SNTB1 on colorectal cancer cell phenotypes and the Wnt/β-catenin/MYC signaling. In conclusion, SNTB1 knockdown inhibits colorectal cancer cell aggressiveness in vitro and tumor growth and metastasis in vivo through the Wnt/β-catenin/MYC signaling; YAP1 might mediate SNTB1 functions on colorectal cancer.

Automatic segmentation of neurovascular bundle on mri using deep learning based topological modulated network

PURPOSE

Radiation damage on neurovascular bundles (NVBs) may be the cause of sexual dysfunction after radiotherapy for prostate cancer. However, it is challenging to delineate NVBs as organ-at-risks from planning CTs during radiotherapy. Recently, the integration of MR into radiotherapy made NVBs contour delineating possible. In this study, we aim to develop an MRI-based deep learning method for automatic NVB segmentation.

METHODS

The proposed method, named topological modulated network, consists of three subnetworks, that is, a focal modulation, a hierarchical block and a topological fully convolutional network (FCN). The focal modulation is used to derive the location and bounds of left and right NVBs', namely the candidate volume-of-interests (VOIs). The hierarchical block aims to highlight the NVB boundaries information on derived feature map. The topological FCN then segments the NVBs inside the VOIs by considering the topological consistency nature of the vascular delineating. Based on the location information of candidate VOIs, the segmentations of NVBs can then be brought back to the input MRI's coordinate system.

RESULTS

A five-fold cross-validation study was performed on 60 patient cases to evaluate the performance of the proposed method. The segmented results were compared with manual contours. The Dice similarity coefficient (DSC) and 95th percentile Hausdorff distance (HD95 ) are (left NVB) 0.81 ± 0.10, 1.49 ± 0.88 mm, and (right NVB) 0.80 ± 0.15, 1.54 ± 1.22 mm, respectively.

CONCLUSION

We proposed a novel deep learning-based segmentation method for NVBs on pelvic MR images. The good segmentation agreement of our method with the manually drawn ground truth contours supports the feasibility of the proposed method, which can be potentially used to spare NVBs during proton and photon radiotherapy and thereby improve the quality of life for prostate cancer patients.

Deep learning-based fast volumetric imaging using kV and MV projection images for lung cancer radiotherapy: A feasibility study

PURPOSE

The long acquisition time of CBCT discourages repeat verification imaging, therefore increasing treatment uncertainty. In this study, we present a fast volumetric imaging method for lung cancer radiation therapy using an orthogonal 2D kV/MV image pair.

METHODS

The proposed model is a combination of 2D and 3D networks. The proposed model consists of five major parts: (1) kV and MV feature extractors are used to extract deep features from the perpendicular kV and MV projections. (2) The feature-matching step is used to re-align the feature maps to their projection angle in a Cartesian coordinate system. By using a residual module, the feature map can focus more on the difference between the estimated and ground truth images. (3) In addition, the feature map is downsized to include more global semantic information for the 3D estimation, which is useful to reduce inhomogeneity. By using convolution-based reweighting, the model is able to further increase the uniformity of image. (4) To reduce the blurry noise of generated 3D volume, the Laplacian latent space loss calculated via the feature map that is extracted via specifically-learned Gaussian kernel is used to supervise the network. (5) Finally, the 3D volume is derived from the trained model. We conducted a proof-of-concept study using 50 patients with lung cancer. An orthogonal kV/MV pair was generated by ray tracing through CT of each phase in a 4D CT scan. Orthogonal kV/MV pairs from nine respiratory phases were used to train this patient-specific model while the kV/MV pair of the remaining phase was held for model testing.

RESULTS

The results are based on simulation data and phantom results from a real Linac system. The mean absolute error (MAE) values achieved by our method were 57.5 HU and 77.4 HU within body and tumor region-of-interest (ROI), respectively. The mean achieved peak-signal-to-noise ratios (PSNR) were 27.6 dB and 19.2 dB within the body and tumor ROI, respectively. The achieved mean normalized cross correlation (NCC) values were 0.97 and 0.94 within the body and tumor ROI, respectively. A phantom study demonstrated that the proposed method can accurately re-position the phantom after shift. It is also shown that the proposed method using both kV and MV is superior to current method using kV or MV only in image quality.

CONCLUSION

These results demonstrate the feasibility and accuracy of our proposed fast volumetric imaging method from an orthogonal kV/MV pair, which provides a potential solution for daily treatment setup and verification of patients receiving radiation therapy for lung cancer.

Effects of Crohn's disease exclusion diet on remission: a systematic review

Background

Dietary therapy may potentially reduce inflammation and promote mucosal healing in patients with Crohn's disease and is associated with fewer side effects and lower cost compared to medical therapy. Recently the Crohn's disease exclusion diet (CDED) has been developed to reduce exposure to individualized dietary components which negatively affect the intestine in patients with Crohn's disease.

Objectives

This systematic review aimed to explore the effectiveness of CDED in Crohn's disease patients.

Design

A systematic review.

Data sources and methods

A systematic search was performed on the PubMed, EBSCOhost, Cochrane library, OVID, Embase, Scopus, and CINHAL to identify relevant clinical trials published from 1 January 2014 to 31 August 2022.

Results

A total of 1120 studies were identified and 7 studies were finally included in the analysis. The study was reported according to Preferred Reporting Items for Systematic Reviews and Meta-analysis statement.

Conclusion

Our findings suggested that the use of CDED seemed to be effective for induction and maintenance of remission in children and adults with mild to moderate Crohn's disease. However, heterogeneity and limitations existed among the studies included. Further investigation in the form of well-designed randomized clinical trials is needed to validate the present findings.

Registration

PROSPERO registration number CRD42022335453.

Comparation of EGFR-TKI (EGFR tyrosine kinase inhibitors) combination therapy and osimertinib for untreated EGFR-mutated advanced non-small cell lung cancers: A systematic review and network meta-analysis

BACKGROUND

EGFR-TKI (tyrosine kinase inhibitor) monotherapy has become the first-line treatment option for patients with EGFR-mutated non-small cell lung cancer (NSCLC). Prolonging the survival time, improving the progression-free survival of front-line treatment, and delaying the occurrence of drug resistance. At present, combination therapy is being widely used. Evaluate the therapeutic effect of TKI joint and Osimertinib drug therapy for positive patients with gene positive.

MATERIAL AND METHODS

Articles that met the inclusion criteria were searched through electronic databases. treatment emergent adverse events were summarized, and progression-free survival (PFS) and overall survival (OS) were calculated. Appropriate networks for different outcomes were created to incorporate all the evidence. Bayesian network-based multitreatment was used to compare the efficacy and specific toxicity of all treatment regimens.

RESULTS

Fourteen eligible studies involving 2325 patients were included. Of these, 7 studies compared EGFR-TKI plus chemotherapy with EGFR-TKI alone, and 6 studies compared EGFR-TKI plus antiangiogenic therapy with EGFR-TKI alone. One study compared Osimertinib and GP, ER, EB, and GCP were more effective than SOC in PFS analysis; however, there was no significant difference between osimertinib and the other 4 combination regimens. The cumulative probabilities of being the most efficacious treatments were (PFS, OS, treatment emergent adverse events): O (73%, 16%, 0%, 0%), GCP (14%, 64%, 10%, 16%), GP (2%, 17%,8%), and EB (3%, 3%, 8%), ER (5%, NA, 4%);GA(1%, NA, 69%).

CONCLUSION

Osimertinib has the lowest side effects and provides better PFS first-line treatment in advanced EGFR-mutated NSCLC.GCP is the best regimen for OS, but its toxicity limits its application, and it may be the first choice for patients with higher survival requirements.

Deep learning-based Fast Volumetric Image Generation for Image-guided Proton FLASH Radiotherapy

Objective

FLASH radiotherapy leverages ultra-high dose-rate radiation to enhance the sparing of organs at risk without compromising tumor control probability. This may allow dose escalation, toxicity mitigation, or both. To prepare for the ultra-high dose-rate delivery, we aim to develop a deep learning (DL)-based image-guide framework to enable fast volumetric image reconstruction for accurate target localization for proton FLASH beam delivery.

Approach

The proposed framework comprises four modules, including orthogonal kV x-ray projection acquisition, DL-based volumetric image generation, image quality analyses, and water equivalent thickness (WET) evaluation. We investigated volumetric image reconstruction using kV projection pairs with four different source angles. Thirty patients with lung targets were identified from an institutional database, each patient having a four-dimensional computed tomography (CT) dataset with ten respiratory phases. Leave-phase-out cross-validation was performed to investigate the DL model's robustness for each patient.

Main results

The proposed framework reconstructed patients' volumetric anatomy, including tumors and organs at risk from orthogonal x-ray projections. Considering all evaluation metrics, the kV projections with source angles of 135° and 225° yielded the optimal volumetric images. The patient-averaged mean absolute error, peak signal-to-noise ratio, structural similarity index measure, and WET error were 75±22 HU, 19±3.7 dB, 0.938±0.044, and -1.3%±4.1%.

Significance

The proposed framework has been demonstrated to reconstruct volumetric images with a high degree of accuracy using two orthogonal x-ray projections. The embedded WET module can be used to detect potential proton beam-specific patient anatomy variations. This framework can rapidly deliver volumetric images to potentially guide proton FLASH therapy treatment delivery systems.

Intermittent Proton Pump Inhibitor Therapy in Low-Risk Non-Variceal Upper Gastrointestinal Bleeding May Be Significantly Cost-Saving

BACKGROUND

High-dose proton pump inhibitor (PPI) therapy, given either intermittently or continuously for non-variceal upper gastrointestinal bleeding (NV-UGIB), is efficacious. Using intermittent PPI for low-risk patients may be cost-saving. Our objective was to estimate the annual cost savings if all low-risk NV-UGIB patients received intermittent PPI therapy.

METHODS

Patients who presented to hospital in Calgary, Alberta, who received a PPI for NV-UGIB from July 2015 to March 2017 were identified using ICD-10 codes. Patients were stratified into no endoscopy, high-risk, and low-risk lesion groups and further subdivided into no PPI, oral PPI, intermittent intravenous (IV), and continuous IV subgroups. Average length of stay (LOS) in each subgroup and costs were calculated.

RESULTS

We identified 4141 patients with NV-UGIBs, (median age 61, 57.4% male). One-thousand two-hundred and thirty-one low-risk patients received continuous IV PPI, with an average LOS of 6.8 days (95% CI 6.2-7.3) versus 4.9 days (95% CI 3.9-5.9) for intermittent IV patients. If continuous IV PPI patients instead received intermittent IV PPI, 3852 patient days and CAD 11,714,390 (2017 CAD)/year could be saved.

CONCLUSIONS

Using real-world administrative data, we demonstrate that a sizable portion of low-risk patients with NV-UGIB who were given continuous IV PPI if switched to intermittent IV therapy could generate significant potential cost savings.

Pan-cancer survey of lncRNA rewiring and functional alternation in tumor-infiltrating T cell by scLNC

Long non-coding RNAs (lncRNAs) have been reported to involve in diverse biological processes, including tumor immunity. Since lncRNAs are expressed with high cell-type specificity, investigation of lncRNAs at the single-cell level will unveil the cell-type-specific functions of lncRNAs. However, at the single-cell level, a systematic pan-cancer analysis of lncRNA functions in tumor immune microenvironments (TIMEs) remains lacking. Here, we performed pan-cancer single-cell profiling of lncRNA functions in TIMEs and developed a tool, scLNC, tailored for lncRNA functional characterization at the single-cell level. scLNC enabled the comparison of lncRNA function from the levels of lncRNA-mRNA pairs, lncRNA regulatory unit activity and unit function in a cell-type-specific manner. Applying scLNC, our analysis depicted the cross-tumor and tumor-specific lncRNA regulatory profiles in the T cell subtypes and revealed the new regulatory units that lncRNAs established in tumor-infiltrating T cells, particularly in the tumor-enriched T cells. We further characterized the activity and functional alternations of lncRNAs through their regulatory units. Overall, our findings suggested that lncRNAs played an important role in the regulation of cytokine production, cell activation and migration in tumor-enriched T cells and further in immunotherapy.

Effect of Stir-Frying on Physicochemical and Functional Properties of Oat Protein Isolates

The heat treatment required for the deactivation of enzymes was carried out on crop species such as oats. Stir-frying, a frequently employed method for enzyme inactivation to preserve their desirable shelf life, can result in diminished nutritional value and protein degeneration. The mechanism by which stir-frying affects the oat protein remains largely unknown. Therefore, this study aimed to investigate the physicochemical and functional properties of the extracted oat protein isolates (OPI) at different stir-frying durations (0, 10, 20, and 30 min) at a temperature of 230 °C. The findings of this study demonstrated that stir-frying led to a decrease in the content of amino acids (AA), potentially attributed to the involvement of certain amino acids in the Maillard reaction. As the time of stir-frying increased, the secondary structure of OPI underwent changes: specifically, β-turns transformed into β-sheets. The process of protein denaturation and redistribution of chemical bonds resulted in an increase in the disulfide bond content of OPI, leading to aggregation, large particle size, and reduced digestibility. However, the water retention properties, foaming properties, and emulsification properties of OPI showed improvement. These findings provide valuable insights for the controlled and precise processing of oats and highlight the potential of OPI as a functional food.

Chloroplast SRP54 and FtsH protease coordinate thylakoid membrane-associated proteostasis in Arabidopsis

Thylakoid membrane protein quality control (PQC), which requires the coordination of membrane protein translocation and degradation of unassembled proteins, determines chloroplast development during de-etiolation. Despite numerous efforts, the regulation of this process in land plants is largely unknown. Here, we report the isolation and characterization of pale green Arabidopsis4 (pga4) mutants in Arabidopsis (Arabidopsis thaliana) with defects in chloroplast development during de-etiolation. Map-based cloning and complementation assays confirmed that PGA4 encodes the chloroplast Signal Recognition Particle 54 kDa (cpSRP54) protein. A heterogeneous Light-Harvesting Chlorophyll a/b Binding-Green Fluorescent Protein (LhcB2-GFP) fusion protein was generated as an indicative reporter for cpSRP54-mediated thylakoid translocation. LhcB2-GFP was dysfunctional and degraded to a short-form dLhcB2-GFP during de-etiolation through an N-terminal degradation initiated on thylakoid membranes. Further biochemical and genetic evidence demonstrated that the degradation of LhcB2-GFP to dLhcB2-GFP was disrupted in pga4 and yellow variegated2 (var2) mutants caused by mutations in the Filamentous Temperature-Sensitive H2 (VAR2/AtFtsH2) subunit of thylakoid FtsH. The yeast two-hybrid assay showed that the N-terminus of LhcB2-GFP interacts with the protease domain of VAR2/AtFtsH2. Moreover, the over-accumulated LhcB2-GFP in pga4 and var2 formed protein aggregates, which were insoluble in mild nonionic detergents. Genetically, cpSRP54 is a suppressor locus for the leaf variegation phenotype of var2. Together, these results demonstrate the coordination of cpSRP54 and thylakoid FtsH in maintaining thylakoid membrane PQC during the assembly of photosynthetic complexes and provide a trackable substrate and product for monitoring cpSRP54-dependent protein translocation and FtsH-dependent protein degradation.

Photothermal Superhydrophobic Chitosan-Based Cotton Fabric for Rapid Deicing and Oil/Water Separation

Superhydrophobic cotton fabrics have a lot of potential for use in practical settings. The majority of superhydrophobic cotton fabrics, however, only serve one purpose and are made from fluoride or silane chemicals. Therefore, it remains a challenge to develop multifunctional superhydrophobic cotton fabrics using environmentally friendly raw materials. In this study, chitosan (CS), amino carbon nanotubes (ACNTs), and octadecylamine (ODA) were used as raw materials to create CS-ACNTs-ODA photothermal superhydrophobic cotton fabrics. The cotton fabric that was created showed a remarkable superhydrophobic property with a water contact angle of 160.3°. The surface temperature of CS-ACNTs-ODA cotton fabric can rise by up to 70 °C when exposed to simulated sunlight, demonstrating the fabric's remarkable photothermal capabilities. Additionally, the coated cotton fabric is capable of quick deicing. Ice particles (10 μL) melted and began to roll down in 180 s under the light of "1 sun". The cotton fabric exhibits good durability and adaptability in terms of mechanical qualities and washing tests. Moreover, the CS-ACNTs-ODA cotton fabric displays a separation efficacy of more than 91% when used to treat various oil and water mixtures. We also impregnate the coating on polyurethane sponges, which can quickly absorb and separate oil and water mixtures.