Effect of initial moisture content, resulting from different ratios of vegetable waste to maize straw, on compost was mediated by composting temperatures and microbial communities at low temperatures

Owing to the huge amounts and perishable character of vegetable wastes, composting is one of the best options for recycling vegetable wastes post-harvest. The initial moisture content (MC) is critical for optimizing composting process, but the effect of high MC in undehydrated vegetable wastes on composting was rarely reported. For this, the plant-scale windrows were prepared by mixing cauliflower waste and maize straw at different ratios to control initial MC of 70 % (T1-70) and 80 % (T2-80), respectively, and composted in winter. As composting progressed, substantial organic matter degradation, progressive humification, decreases in electrical conductivity and increases of pH and germination index (GI) were observed in both treatments. Nonetheless, T1-70 accelerated heating rate early during composting, prolonged high temperature period (>50 °C) by 30 d, thus increased the harmless level of composting, and significantly improved the humification of end-products compared to T2-80. Results also revealed that T1-70 activated more indigenous microbes and enhanced microbial interactions early during composting, with the fungi enriched in T1-70 playing an important role in accelerating the composting process. Remarkably, the difference in composting temperatures, humification degree, and microbial communities between the two treatments was most significant during the maturation phase. In this phase, MWH_CFBk5, Planktosalinus, Pseudopedobacter, and Luteimonas enriched in T1-70 were positively correlated with humification indices. It is suggested that the effect of initial MC, resulting from different ratios of vegetable waste to maize straw, on their composting was mediated by the composting temperature and microbial communities at low temperatures.

BCKDK Modification Enhances the Anticancer Efficacy of CAR-T Cells by Reprogramming Branched Chain Amino Acid Metabolism

Altered Branched Chain Amino Acids (BCAA), including leucine, isoleucine and valine, are frequently observed in patients with advanced cancer. We evaluated the efficacy of Chimeric Antigen Receptor (CAR) T cell-mediated cancer cell lysis potential in the immune microenvironment of BCAA supplementation and deletion. BCAA supplementation increased cancer cell killing percentage, while accelerating BCAA catabolism and deceasing BCAA transporter decreased cancer cell lysis efficacy. We thus designed BCKDK engineering CAR T cells for the reprogramming of BCAA metabolism in the tumor microenvironment based on the genotype and phenotype modification. BCKDK overexpression (OE) in CAR-T cells significantly improved cancer cell lysis, while BCKDK knockout (KO) resulted in inferior lysis potential. In an in vivo experiment, BCKDK-OE CAR-T cells treatment significantly prolonged the survival of mice bearing NALM6-GL cancer cells, with the differentiation of central memory cells and the increasing proportion of CAR-T cells in peripheral circulation. BCKDK-KO CAR-T cells treatment resulted in shorter survival and decreasing percentage of CAR-T cells in peripheral circulation. In conclusion, BCKDK engineered CAR-T cells exert distinct phenotype for the superior anticancer efficiency.

Dl-3-n-butylphthalide promotes microglial phagocytosis and inhibits microglial inflammation via regulating AGE-RAGE pathway in APP/PS1 mice

Alzheimer's disease (AD) stands as the most prevalent neurodegenerative condition worldwide, and its correlation with microglial function is notably significant. Dl-3-n-butylphthalide (NBP), derived from the seeds of Apium graveolens L. (Chinese celery), has demonstrated the capacity to diminish Aβ levels in the brain tissue of Alzheimer's transgenic mice. Despite this, its connection to neuroinflammation and microglial phagocytosis, along with the specific molecular mechanism involved, remains undefined. In this study, NBP treatment exhibited a substantial improvement in learning deficits observed in AD transgenic mice (APP/PS1 transgenic mice). Furthermore, NBP treatment significantly mitigated the total cerebral Aβ plaque deposition. This effect was attributed to the heightened presence of activated microglia surrounding Aβ plaques and an increase in microglial phagocytosis of Aβ plaques. Transcriptome sequencing analysis unveiled the potential involvement of the AGE (advanced glycation end products) -RAGE (receptor for AGE) signaling pathway in NBP's impact on APP/PS1 mice. Subsequent investigation disclosed a reduction in the secretion of AGEs, RAGE, and proinflammatory factors within the hippocampus and cortex of NBP-treated APP/PS1 mice. In summary, NBP alleviates cognitive impairment by augmenting the number of activated microglia around Aβ plaques and ameliorating AGE-RAGE-mediated neuroinflammation. These findings underscore the related mechanism of the crucial neuroprotective roles of microglial phagocytosis and anti-inflammation in NBP treatment for AD, offering a potential therapeutic target for the disease.

Glycogen synthesis is required for adaptive thermogenesis in beige adipose tissue and affects diet-induced obesity

Glycogen is a form of energy storage for glucose in different tissues such as liver and skeletal muscle. It remains incompletely understood how glycogen impacts on adipose tissue functionality. Cold exposure elevated the expression of Gys1 that encodes glycogen synthase 1 in brown adipose tissue (BAT) and inguinal white adipose tissue (iWAT). The in vivo function of Gys1 was analyzed using a mouse model in which Gys1 was deleted specifically in adipose tissues. Under normal chow conditions, Gys1 deletion caused little changes to body weight and glucose metabolism. Deletion of Gys1 abrogated upregulation of UCP1 and other thermogenesis-related genes in iWAT upon prolonged cold exposure or treatment with β3-adrenergic receptor agonist CL-316,243. Stimulation of UCP1 by CL-316,243 in adipose-derived stromal cells (stromal vascular fractions, SVFs) was also reduced by Gys1 deletion. Both the basal glycogen content and CL-316,243-stimulated glycogen accumulation in adipose tissues were reduced by Gys1 deletion. High-fat diet-induced obesity and insulin resistance were aggravated in Gys1-deleted mice. The loss of body weight upon CL-316,243 treatment was also abrogated by the loss of Gys1. In conclusion, our results underscore the pivotal role of glycogen synthesis in adaptive thermogenesis in beige adipose tissue and its impact on diet-induced obesity in mice.NEW & NOTEWORTHY Glycogen is one of major types of fuel reserve in the body and its classical function is to maintain blood glucose level. This study uncovers that glycogen synthesis is required for beige fat tissue to generate heat upon cold exposure. Such a function of glycogen is linked to development of high-fat diet-induced obesity, thus extending our understanding about the physiological functions of glycogen.

Effect of zein-pectin composite particles on the stability and rheological properties of gelatin/hydroxypropyl methylcellulose water-water systems

To improve the compatibility of gelatin (GA) and hydroxypropyl methylcellulose (HPMC), we investigated the effects of zein-pectin composite particles (ZCPs) with various zein/pectin ratios (1:0, 1:0.5, 1:1, 1:1.5, and 1:2) on the physical stability, microstructure, and rheological properties of the GA/HPMC water-water systems. With increasing pectin ratio, the particle size of the composite particles increased from 234.53 ± 1.48 nm to 1111.00 ± 26.91 nm, and their zeta potential decreased from 20.60 mV to below -34.77 mV. Macroscopic and microstructure observations indicated that pectin-modified ZCPs could effectively inhibit phase separation behavior between GA and HPMC. Compared to pure HPMC, the GA/HPMC water-water systems possessed a higher viscosity and dynamic modulus at room temperatures but lower gel temperatures (reduction of about 11 %). The viscosity and modulus of the water-water systems increased with increasing pectin ratio in ZCPs. However, the ratio had no impact on the gel-sol (sol-gel) transition temperatures (not statistically significant (P < 0.05)). This study may serve as a reference for advancing the processability of HPMC.

Analysis of Ionomic Profiles of Spinal Cords in a Rat Model with Bone Cancer Pain

Background

Ionomics is used to study levels of ionome in different states of organisms and their correlations. Bone cancer pain (BCP) severely reduces quality of life of patients or their lifespan. However, the relationship between BCP and ionome remains unclear.

Methods

The BCP rat model was constructed through inoculation of Walker 256 cells into the left tibia. Von Frey test, whole-cell patch-clamp recording and inductively coupled plasma mass spectrometry (ICP-MS) technologies were conducted for measuring tactile hypersensitivity, the frequency and amplitude of miniature excitatory postsynaptic currents (mEPSCs) of neurons of spinal slices, and ionome of spinal cord samples, respectively. Principal component analysis (PCA) was used to explore ionomic patterns of the spinal cord.

Results

The BCP rat model was successfully constructed through implantation of Walker 256 cells into the left tibia. The frequency and amplitude of mEPSCs of neurons in the spinal cord slices from the BCP model rats were notably greater than those in the sham control. In terms of ionomics, the spinal cord levels of two macroelements (Ca and S), four microelements (Fe, Mn, Li and Sr) and the toxic element Ti in the BCP group of rats were significantly increased by inoculation of Walker 256 cancer cells, compared to the sham control. In addition, the correlation patterns between the elements were greatly changed between the sham control and BCP groups. PCA showed that inoculation of Walker 256 cells into the tibia altered the overall ionomic profiles of the spinal cord. There was a significant separation trend between the two groups.

Conclusion

Taken together, inoculation of Walker 256 cells into the left tibia contributes to BCP, which could be closely correlated by some elements. The findings provided novel information on the relationship between the ionome and BCP.

Enhanced YOLO v3 for precise detection of apparent damage on bridges amidst complex backgrounds

A bridge disease identification approach based on an enhanced YOLO v3 algorithm is suggested to increase the accuracy of apparent disease detection of concrete bridges under complex backgrounds. First, the YOLO v3 network structure is enhanced to better accommodate the dense distribution and large variation of disease scale characteristics, and the detection layer incorporates the squeeze and excitation (SE) networks attention mechanism module and spatial pyramid pooling module to strengthen the semantic feature extraction ability. Secondly, CIoU with better localization ability is selected as the loss function for training. Finally, the K-means algorithm is used for anchor frame clustering on the bridge surface disease defects dataset. 1363 datasets containing exposed reinforcement, spalling, and water erosion damage of bridges are produced, and network training is done after manual labelling and data improvement in order to test the efficacy of the algorithm described in this paper. According to the trial results, the YOLO v3 model has enhanced more than the original model in terms of precision rate, recall rate, Average Precision (AP), and other indicators. Its overall mean Average Precision (mAP) value has also grown by 5.5%. With the RTX2080Ti graphics card, the detection frame rate increases to 84 Frames Per Second, enabling more precise and real-time bridge illness detection.

Notoginsenoside R1 targets PPAR-γ to inhibit hepatic stellate cell activation and ameliorates liver fibrosis

BACKGROUND

Hepatic fibrosis, a common pathological process that occurs in end-stage liver diseases, is a serious public health problem and lacks effective therapy. Notoginsenoside R1 (NR1) is a small molecule derived from the traditional Chinese medicine Sanqi, exhibiting great potential in treating diverse metabolie disorders. Here we aimed to enquired the role of NR1 in liver fibrosis and its underlying mechanism in hepatoprotective effects.

METHODS

We investigated the anti-fibrosis effect of NR1 using CCl4-induced mouse mode of liver fibrosis as well as TGF-β1-activated JS-1, LX-2 cells and primary hepatic stellate cell. Cell samples treated by NR1 were collected for transcriptomic profiling analysis. PPAR-γ mediated TGF-β1/Smads signaling was examined using PPAR-γ selective inhibitors and agonists intervention, immunofluorescence staining and western blot analysis. Additionally, we designed and studied the binding of NR1 to PPAR-γ using molecular docking.

RESULTS

NR1 obviously attenuated liver histological damage, reduced serum ALT, AST levels, and decreased liver fibrogenesis markers in mouse mode. Mechanistically, NR1 elevated PPAR-γ and decreased TGF-β1, p-Smad2/3 expression. The TGF-β1/Smads signaling pathway and fibrotic phenotype were altered in JS-1 cells after using PPAR-γ selective inhibitors and agonists respectively, confirming PPAR-γ played a pivotal protection role inNR1 treating liver fibrosis. Further molecular docking indicated NR1 had a strong binding tendency to PPAR-γ with minimum free energy.

CONCLUSIONS

NR1 attenuates hepatic stellate cell activation and hepatic fibrosis by elevating PPAR-γ to inhibit TGF-β1/Smads signalling. NR1 may be a potential candidate compound for reliving liver fibrosis.

A phase I study to evaluate the safety, pharmacokinetics, and pharmacodynamics of PF-06939999 (PRMT5 inhibitor) in patients with selected advanced or metastatic tumors with high incidence of splicing factor gene mutations

BACKGROUND

Protein arginine methyltransferase 5 (PRMT5) methylates multiple substrates dysregulated in cancer, including spliceosome machinery components. PF-06939999 is a selective small-molecule PRMT5 inhibitor.

PATIENTS AND METHODS

This phase I dose-escalation and -expansion trial (NCT03854227) enrolled patients with selected solid tumors. PF-06939999 was administered orally once or twice a day (q.d./b.i.d.) in 28-day cycles. The objectives were to evaluate PF-06939999 safety and tolerability to identify maximum tolerated dose (MTD) and recommended part 2 dose (RP2D), and assess pharmacokinetics (PK), pharmacodynamics [changes in plasma symmetric dimethylarginine (SDMA) levels], and antitumor activities.

RESULTS

In part 1 dose escalation, 28 patients received PF-06939999 (0.5 mg q.d. to 6 mg b.i.d.). Four of 24 (17%) patients reported dose-limiting toxicities: thrombocytopenia (n = 2, 6 mg b.i.d.), anemia (n = 1, 8 mg q.d.), and neutropenia (n = 1, 6 mg q.d.). PF-06939999 exposure increased with dose. Steady-state PK was achieved by day 15. Plasma SDMA was reduced at steady state (58%-88%). Modulation of plasma SDMA was dose dependent. No MTD was determined. In part 2 dose expansion, 26 patients received PF-06939999 6 mg q.d. (RP2D). Overall (part 1 + part 2), the most common grade ≥3 treatment-related adverse events included anemia (28%), thrombocytopenia/platelet count decreased (22%), fatigue (6%), and neutropenia (4%). Three patients (6.8%) had confirmed partial response (head and neck squamous cell carcinoma, n = 1; non-small-cell lung cancer, n = 2), and 19 (43.2%) had stable disease. No predictive biomarkers were identified.

CONCLUSIONS

PF-06939999 demonstrated a tolerable safety profile and objective clinical responses in a subset of patients, suggesting that PRMT5 is an interesting cancer target with clinical validation. However, no predictive biomarker was identified. The role of PRMT5 in cancer biology is complex and requires further preclinical, mechanistic investigation to identify predictive biomarkers for patient selection.

Comparative Study of Ultrasonic Vibration-Assisted Die-Sinking Micro-Electrical Discharge Machining on Polycrystalline Diamond and Titanium

Die-sinking micro-electrical discharge machining (micro-EDM) is a potential method used to fabricate intricate structures without complex electrode motion planning and compensation. However, machining efficiency and poor discharge states are still bottlenecks. This study conducted a comparative investigation into the impact of ultrasonic vibration on die-sinking micro-EDM of polycrystalline diamond (PCD) and pure titanium (TA2). By adjusting discharge parameters, this study systematically evaluated the influence of ultrasonic vibration on these two materials based on discharge waveforms, motion trajectories, effective discharge counts and groove profiles. At an open-circuit voltage of 100 V, ultrasonic vibration promotes die-sinking micro-EDM of PCD. However, when the open-circuit voltage increases to 200 V, ultrasonic vibration exhibits inhibitory effects in general. Conversely, for TA2, ultrasonic vibration shows a promoting effect at both voltages, indicating the differences of ultrasonic vibration-assisted die-sinking micro-EDM on PCD and TA2. For PCD, ultrasonic cavitation improves the discharge gap environment, accelerating the removal of discharge debris. For TA2, due to its poor thermal conductivity, ultrasonic cavitation acts to break the arc, accelerating heat transfer. These research findings provide guidance for ultrasonic vibration-assisted die-sinking micro-EDM in industrial applications.

Ultra short term power load forecasting based on the fusion of Seq2Seq BiLSTM and multi head attention mechanism

Ultra-short-term power load forecasting is beneficial to improve the economic efficiency of power systems and ensure the safe and stable operation of power grids. As the volatility and randomness of loads in power systems, make it difficult to achieve accurate and reliable power load forecasting, a sequence-to-sequence based learning framework is proposed to learn feature information in different dimensions synchronously. Convolutional Neural Networks(CNN) Combined with Bidirectional Long Short Term Memory(BiLSTM) Networks is constructed in the encoder to extract the correlated timing features embedded in external factors affecting power loads. The parallel BiLSTM network is constructed in the decoder to mine the power load timing information in different regions separately. The multi-headed attention mechanism is introduced to fuse the BiLSTM hidden layer state information in different components to further highlight the key information representation. The load forecastion results in different regions are output through the fully connected layer. The model proposed in this paper has the advantage of high forecastion accuracy through the example analysis of real power load data.

An efficient genetic transformation system mediated by Rhizobium rhizogenes in fruit trees based on the transgenic hairy root to shoot conversion

Genetic transformation is a critical tool for gene editing and genetic improvement of plants. Although many model plants and crops can be genetically manipulated, genetic transformation systems for fruit trees are either lacking or perform poorly. We used Rhizobium rhizogenes to transfer the target gene into the hairy roots of Malus domestica and Actinidia chinensis. Transgenic roots were generated within 3 weeks, with a transgenic efficiency of 78.8%. Root to shoot conversion of transgenic hairy roots was achieved within 11 weeks, with a regeneration efficiency of 3.3%. Finally, the regulatory genes involved in stem cell activity were used to improve shoot regeneration efficiency. MdWOX5 exhibited the most significant effects, as it led to an improved regeneration efficiency of 20.6% and a reduced regeneration time of 9 weeks. Phenotypes of the overexpression of RUBY system mediated red roots and overexpression of MdRGF5 mediated longer root hairs were observed within 3 weeks, suggesting that the method can be used to quickly screen genes that influence root phenotype scores through root performance, such as root colour, root hair, and lateral root. Obtaining whole plants of the RUBY system and MdRGF5 overexpression lines highlights the convenience of this technology for studying gene functions in whole plants. Overall, we developed an optimized method to improve the transformation efficiency and stability of transformants in fruit trees.

Investigating the epidemiological relevance of secretory otitis media and neighboring organ diseases through an Internet search

Background

This study examined the epidemiological correlations between secretory otitis media (SOM) and diseases of neighboring organs. We measured changes in disease incidences during the 2020 COVID-19 pandemic using Internet big data spanning from 2011 to 2021.

Methods

This study used the Baidu Index (BI) to determine the search volume for the terms "secretory otitis media (SOM)", "tonsillitis", "pharyngolaryngitis", "adenoid hypertrophy (AH)", "nasopharyngeal carcinoma (NPC)", "nasal septum deviation (NSD)", "rhinosinusitis", "allergic rhinitis (AR)", and "gastroesophageal reflux disease (GERD)" in Mandarin from January 2011 to December 2021. The correlations between these terms were analyzed using Spearman's correlation coefficients. The results were compared search data from 2019 and 2021 to assess the effects of isolation on SOM in 2020.

Results

The seasonal variations trends of SOM and other diseases coincided well (P < 0.05), except for AR. During the 11-year timeframe, the monthly searches for rhinosinusitis, NSD, tonsillitis, pharyngolaryngitis, and NPC were statistically correlated with SOM (R = 0.825, 0.594, 0.650, 0.636, 0.664, respectively; P < 0.05). No correlation was found between SOM and AR, SOM and AH, or SOM and GERD (R =  - 0.028, R = 0.259, R = 0.014, respectively, P > 0.05). The total search volumes for SOM, rhinosinusitis, NPC, and AH decreased in 2020 compared to 2019.

Discussion

SOM exhibited a discernible epidemiological connection with rhinosinusitis, nasal septal deviation (NSD), tonsillitis, pharyngolaryngitis, and nasopharyngeal carcinoma (NPC). A decrease in public gatherings was observed to effectively reduce the incidences of SOM. This underscores the pivotal role of social measures in influencing the prevalence of SOM and emphasizes the intricate interplay between SOM and various associated health factors, with implications for public health strategies.

State of health estimation of LIB based on discharge section with multi-model combined

Accurate estimation of a battery's state of health (SOH) is essential in battery management systems (BMS). This study considers a complete analysis of combining incremental capacity (IC), differential thermal voltammetry (DTV), and differential temperature (DT) for SOH prediction in cases of discharge. Initially, the IC, DTV, and DT curves were derived from the current, voltage, and temperature datasets, and these curves underwent smoothing through the application of Lowess and Gaussian techniques. Subsequently, discerning healthy features were identified within the domains where the curve exhibited substantial phase transitions. Utilizing Pearson correlation analysis, features exhibiting the utmost correlation with battery capacity degradation were singled out. Finally, the state-of-health (SOH) prediction model was constructed using a bidirectional long short-term memory (BILSTM) neural network. Two datasets were used to validate the model, and the experimental results demonstrated that the SOH prediction had a root mean square error (RMSE) below 1.2% and mean absolute error (MAE) below 1%, which verified the feasibility and accuracy. This approach quantifies the internal electrochemical reactions of a battery using externally measured data, further enabling early SOH predictions.

Self-esteem and cortical thickness correlate with aggression in healthy children: A surface-based analysis

Aggressive behavior can have serious physical, psychological, and social consequences. However, little is known about the personality and neurological antecedents underlying aggressive behavior in children. The objective of this study was to investigate the relationship between self-esteem, aggression, and brain structure (i.e., cortical thickness and surface area) in a population of healthy children (N = 78; 9-12 years; mean age: 9.95 ± 0.90 years). The results revealed that self-esteem showed a negative association with aggression and significantly predicted aggressive behavior. No gender differences were found in aggression and its neural correlates. We performed the cortical parcellation method to further explore the neural foundations underlying the association of self-esteem with aggression. Children with higher aggression had increased cortical thickness in four clusters after multiple comparison correction: right medial orbitofrontal cortex, right lateral orbitofrontal cortex, right superior frontal gyrus, and left insula. In a mediation analysis, cortical thickness in the right medial orbitofrontal cortex contributed to the effect of self-esteem on aggression. These findings extend our understanding of morphological correlates of aggression in children, suggesting that an increased cortical thickness in childhood is a potential mechanism linking low self-esteem to aggression.

Longitudinal Relationships Between School Climate, Academic Achievement, and Gaming Disorder Symptoms Among Chinese Adolescents

Despite growing concerns regarding the development of gaming disorder symptoms among adolescents, the longitudinal relationship between school factors and gaming disorder symptoms remains far from being fully understood. This two-year longitudinal study examined the relationship between school climate perceptions, academic achievement, and gaming disorder symptoms among three distinct demographic cohorts: preadolescents (n = 1513; 46.9% girls, Mage = 10.64 years, SD = 0.56), early adolescents (n = 1771; 48.3% girls, Mage = 13.54 years, SD = 0.70), and late adolescents (n = 2385; 50.1% girls, Mage = 16.41 years, SD = 0.59). A four-wave study was conducted (six months apart) using random intercept cross-lagged panel models (RI-CLPMs) to separate the within-person (state level) from the between-person (trait level) effects. The results obtained from the RI-CLPMs indicated that fluctuations in school climate perceptions negatively predicted subsequent changes in gaming disorder symptoms among preadolescents at the within-person level, but not among early and late adolescents. Fluctuations relating to gaming disorder symptoms also negatively predicted subsequent changes regarding academic achievement in late adolescents, but not in preadolescents and early adolescents. The effect of school-related factors on gaming disorder symptoms varies across different developmental stages. While preadolescents may represent a particularly susceptible subgroup for gaming disorder in terms of being predicted by their school environment, late adolescents appear to be more vulnerable to predictors of gaming disorder symptoms. The current study also discusses the implications of school-wide programs aimed at improving school climate and preventing the development of gaming disorder symptoms during key developmental periods.

Untargeted urine metabolomics and machine learning provide potential metabolic signatures in children with autism spectrum disorder

Background

Complementary to traditional biostatistics, the integration of untargeted urine metabolomic profiling with Machine Learning (ML) has the potential to unveil metabolic profiles crucial for understanding diseases. However, the application of this approach in autism remains underexplored. Our objective was to delve into the metabolic profiles of autism utilizing a comprehensive untargeted metabolomics platform coupled with ML.

Methods

Untargeted metabolomics quantification (UHPLC/Q-TOF-MS) was performed for urine analysis. Feature selection was conducted using Lasso regression, and logistic regression, support vector machine, random forest, and extreme gradient boosting were utilized for significance stratification. Pathway enrichment analysis was performed to identify metabolic pathways associated with autism.

Results

A total of 52 autistic children and 40 typically developing children were enrolled. Lasso regression identified ninety-two urinary metabolites that significantly differed between the two groups. Distinct metabolites, such as prostaglandin E2, phosphonic acid, lysine, threonine, and phenylalanine, were revealed to be associated with autism through the application of four different ML methods (p<0.05). The alterations observed in the phosphatidylinositol and inositol phosphate metabolism pathways were linked to the pathophysiology of autism (p<0.05).

Conclusion

Significant urinary metabolites, including prostaglandin E2, phosphonic acid, lysine, threonine, and phenylalanine, exhibit associations with autism. Additionally, the involvement of the phosphatidylinositol and inositol phosphate pathways suggests their potential role in the pathophysiology of autism.

Dual-constrained physics-enhanced untrained neural network for lensless imaging

An untrained neural network (UNN) paves a new way to realize lensless imaging from single-frame intensity data. Based on the physics engine, such methods utilize the smoothness property of a convolutional kernel and provide an iterative self-supervised learning framework to release the needs of an end-to-end training scheme with a large dataset. However, the intrinsic overfitting problem of UNN is a challenging issue for stable and robust reconstruction. To address it, we model the phase retrieval problem into a dual-constrained untrained network, in which a phase-amplitude alternating optimization framework is designed to split the intensity-to-phase problem into two tasks: phase and amplitude optimization. In the process of phase optimization, we combine a deep image prior with a total variation prior to retrain the loss function for the phase update. In the process of amplitude optimization, a total variation denoising-based Wirtinger gradient descent method is constructed to form an amplitude constraint. Alternative iterations of the two tasks result in high-performance wavefield reconstruction. Experimental results demonstrate the superiority of our method.

Optical transmission of microwave control signal towards large-scale superconducting quantum computing

With the rapid development of superconducting quantum computing and the implementation of surface code, large-scale quantum computing is emerging as an urgent demand. In a superconducting computing system, the qubit is maintained in a cryogenic environment to avoid thermal excitation. Thus, the transmission of control signals, which are generated at room temperature, is needed. Typically, the transmission of these signals to the qubit relies on a coaxial cable wiring approach. However, in a large-scale computing system with hundreds or even thousands of qubits, the coaxial cables will pose great space and heat load to the dilution refrigerator. Here, to tackle this problem, we propose and demonstrate a direct-modulation-based optical transmission line. In our experiment, the average single-qubit XEB error and control error are measured as 0.139% and 0.014% separately, demonstrating the feasibility of the optical wiring approach and paving the way for large-scale superconducting quantum computing.

Interfacial electric field construction of hollow PdS QDs/Zn1-xCdxS solid solution with enhanced photocatalytic hydrogen evolution

The regulation of hollow morphology, band structure modulation of solid solution, and introduction of cocatalysts greatly promote the separation of electron-hole pairs in photocatalytic processes, which is of great significance for the process of photocatalytic hydrogen evolution (PHE). In this study, we constructed Zn1-xCdxS hollow solid solution photocatalysts using template and ion exchange methods, and successfully loaded PdS quantum dots (PdS QDs) onto the solid solution through in situ sulfidation. Significantly, the 0.5 wt% PdS QDs/Zn0.6Cd0.4S composite material achieved a H2 production rate of 27.63 mmol g-1 h-1 in the PHE process. The hollow structure of the composite material enhances processes such as light reflection and scattering, the band structure modulation of the solid solution enables the electron-hole pairs to reach an optimal exciton recombination balance, and the modification of PdS QDs provides abundant sites for oxidation, thereby promoting the proton reduction and hydrogen evolution rate. This work provides valuable guidance for the rational design of efficient composite PHE catalysts with strong internal electric field.

Pathogen Discovery in the Post-COVID Era

Pathogen discovery plays a crucial role in the fields of infectious diseases, clinical microbiology, and public health. During the past four years, the global response to the COVID-19 pandemic highlighted the importance of early and accurate identification of novel pathogens for effective management and prevention of outbreaks. The post-COVID era has ushered in a new phase of infectious disease research, marked by accelerated advancements in pathogen discovery. This review encapsulates the recent innovations and paradigm shifts that have reshaped the landscape of pathogen discovery in response to the COVID-19 pandemic. Primarily, we summarize the latest technology innovations, applications, and causation proving strategies that enable rapid and accurate pathogen discovery for both acute and historical infections. We also explored the significance and the latest trends and approaches being employed for effective implementation of pathogen discovery from various clinical and environmental samples. Furthermore, we emphasize the collaborative nature of the pandemic response, which has led to the establishment of global networks for pathogen discovery.

Determination of dimethylated nucleosides in serum from colorectal cancer patients by hydrophilic interaction liquid chromatography-tandem mass spectrometry

RNA modifications play a crucial regulatory role in a variety of biological processes and are closely related to numerous diseases, including cancer. The diversity of metabolites in serum makes it a favored biofluid for biomarkers discovery. In this work, a robust and accurate hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS) approach was established for simultaneous determination of dimethylated nucleosides in human serum. Using the established method, we were able to accurately quantify the concentrations of N6-2'-O-dimethyladenosine (m6Am), N2,N2-dimethylguanosine (m2,2G), and 5,2'-O-dimethyluridine (m5Um) in serum samples from 53 healthy controls, 57 advanced colorectal adenoma patients, and 39 colorectal cancer (CRC) patients. The results showed that, compared with healthy controls and advanced colorectal adenoma patients, the concentrations of m6Am and m2,2G were increased in CRC patients, while the concentration of m5Um was decreased in CRC patients. These results indicate that these three dimethylated nucleosides could be potential biomarkers for early detection of colorectal cancer. Interestingly, the level of m5Um was gradually decreased from healthy controls to advanced colorectal adenoma patients to CRC patients, indicating m5Um could also be used to evaluate the level of malignancy of colorectal tumor. In addition, this study will contribute to the investigation on the regulatory mechanisms of RNA dimethylation in the onset and development of colorectal cancer.

Evaluating the symmetric and asymmetric effectiveness of low carbon energy consumption for ecological footprint in China: the role of environment-related technological innovation

The objective of this study is to scrutinize the impact of low carbon energy consumption, environmental-related technological innovation, urbanization, economic growth, and trade on China's ecological footprint from 1980 to 2021. To investigate the nature of the long-term connections between the variables, we employ the symmetric and asymmetric autoregressive distributed lag (ARDL) technique to explore the long- and short-run elasticities of coefficients. The results of ARDL and NARDL verified the environmental Kuznets curve (EKC) hypothesis in the long run in the presence of low carbon energy consumption. Moreover, the findings show that the positive part of low carbon energy consumption is negatively connected with the ecological footprint. Alternatively, the positive part of low carbon energy consumption is positively linked with the ecological footprint. The outcome highlights that environment-related technological innovation reduces the level of ecological footprint. Similarly, urbanization has a detrimental effect on the ecological footprint. Based on the estimated findings, it is suggested that China's economy should place a greater emphasis on increasing its level of investment in the low carbon energy sector and adopting severe environmental legislation to protect the economy from environmental burden.

Bckdk-Mediated Branch Chain Amino Acid Metabolism Reprogramming Contributes to Muscle Atrophy during Cancer Cachexia

SCOPE

Branched chain amino acids (BCAAs) are essential amino acids and important nutrient signals for energy and protein supplementation. The study uses muscle-specific branched-chain α-keto acid dehydrogenase kinase (Bckdk) conditional knockout (cKO) mice to reveal the contribution of BCAA metabolic dysfunction to muscle wasting.

METHOD AND RESULTS

Muscle-specific Bckdk-cKO mice are generated through crossbreeding of Bckdkf/f mice with Myf5Cre mice. Lewis lung cancer (LLC) tumor transplantation is used to establish the cancer cachexia model. The occurrence of cancer cachexia is accelerated in the muscle-specific Bckdk-cKO mice after bearing LLC tumor. Wasting skeletal muscle is characterized by increased protein ubiquitination degradation and impaired protein synthesis. The wasting muscle gastrocnemius is mechanized as a distinct BCAA metabolic dysfunction. Based on the atrophy phenotype resulting from BCAA metabolism dysfunction, the optimized BCAA supplementation improves the survival of cancer cachexia in muscle-specific Bckdk-cKO mice bearing LLC tumors, and improves the occurrence of cancer cachexia. The mechanism of BCAA supplementation on muscle mass preservation is based on the promotion of protein synthesis and the inhibition of protein ubiquitination degradation.

CONCLUSIONS

Dysfunctional BCAA metabolism contributes to the inhibition of protein synthesis and increases protein degradation in the cancer cachexia model of muscle-specific Bckdk-cKO mice bearing LLC tumors. The reprogramming of BCAA catabolism exerts therapeutic effects by stimulating protein synthesis and inhibiting protein degradation in skeletal muscle.

New Wine in an Old Bottle? Exposure to Bullying-Related Media and Bullying Perpetration Behavior in Daily Life Among Adolescents

Although the effect of media violence on aggression has garnered major attention, little is known about the link between bullying-related media exposure and bullying behaviors. Across three studies, we examined this association among Chinese adolescents. Study 1 used a large sample of adolescents (n=10,391, 51.4% boys) to investigate the link between bullying-related media exposure and bullying perpetration. Using another adolescent sample (n=3,125, 49.5% boys), Study 2 replicated the findings from Study 1 and extended the investigation from traditional bullying to cyberbullying perpetration. Study 3 examined the longitudinal associations between bullying-related media exposure and (cyber)bullying perpetration 6 months later (n = 2,744, 47.0% boys). The results suggested a positive, albeit small, association between exposure to bullying-related media and (cyber)bullying perpetration. Importantly, personal anti-bullying attitudes moderated this link, with a significant association observed among adolescents holding weak anti-bullying attitudes. Findings are discussed with respect to the media's effect on bullying behaviors.

An Investigation in Sub-Millimeter Channel Fabrication by the Non-Aqueous Electrolyte Jet Machining of Zr-Based Bulk Metallic Glasses

Zr-based bulk metallic glasses (BMGs) have many unique properties. Due to their excellent performance and manufacturing process, they have become a research focus in the material science community. Electrolyte Jet Machining (EJM) is a non-contact electrochemical processing method with high surface integrity and high material removal rate (MRR). In this research, the sub-millimeter channels fabricated by EJM on Zr-based BMGs have been studied to explore the dissolution mechanisms and surface integrity under different scanning rates and voltages. The results show that, with other machining parameters holding constant, an increase in voltage leads to a substantial enhancement in both the depth and width of the channels machined on Zr-based BMGs. Notably, the influence of voltage on the depth of the channels is particularly pronounced. Additionally, an escalation in scanning rate correlates with a decrease in channel depth, with minimal variation in channel width. This study indicates that alcohol-based EJM is an effective method to fabricate sub-millimeter channels and modulate structures on Zr-based BMGs.

Effects of alkaline mineral complex supplementation on production performance, serum variables, and liver transcriptome in calves

Calf diarrhea causes huge economic losses to livestock due to its high incidence and mortality rates. Alkaline mineral complex water is an alkaline solution containing silicon, sodium, potassium, zinc, and germanium, and has biological benefits and therapeutic effects. This study aimed to evaluate the impact of alkaline mineral complex water supplementation on the health of calves and to investigate the effect of Alkaline mineral complex water supplementation on neonatal calf serum variables and the liver transcriptome. Sixty Holstein calves (age 1.88 ± 0.85 days, weight 36.63 ± 3.34 kg) were selected and randomly divided into two groups: the T group (treatment group with alkaline mineral complex water supplemented during the experiment) and C group (control group without alkaline mineral complex water supplementation). Alkaline mineral complex water supplementation significantly increased the body weight for calves aged 60 d and average daily gain during the experimental period (1-60 d). In addition, Alkaline mineral complex water supplementation could significantly decrease the diarrhea rate for calves aged 16-30 d, enhance the T-AOC, IgG, IGF-1, and IGFBP-2 in concentrations. The results of KEGG enrichment analysis in transcriptomics indicate that Alkaline mineral complex water supplementation inhibited the target IL-1B gene of the NF-kappa B signaling pathway of liver. Alkaline mineral complex water supplementation decreased calf diarrhea and improved partial immune function, anti-inflammatory activity, antioxidant capacity, and health of calves. Alkaline mineral complex is a candidate to replace medicated feed additives. Alkaline mineral complex waterAlkaline mineral complex waterAlkaline mineral complex waterAlkaline mineral complex waterAlkaline mineral complex waterAlkaline mineral complex waterAlkaline mineral complex water.

The mating system of Himalayan marmots as inferred by microsatellite markers

The Himalayan marmot Marmota himalayana is widely distributed across the Qinghai-Tibetan Plateau and lives in social groups, yet the mating system of this highly social marmot species is unknown. In this study, the genetic mating system of Himalayan marmots was investigated using microsatellite markers to determine which mating strategies individuals employ. Results revealed that both monogamous and polygamous mating relationships occur in our study population, indicating that the genetic mating system of this marmot species is promiscuity. This study presents the first genetic evidence on the mating system for Himalayan marmots, yet indicates that further studies employing both a genetic and behavioral framework are needed to better understand the social structure and reproductive biology of this marmot species.

AI's deep dive into complex pediatric inguinal hernia issues: a challenge to traditional guidelines?

OBJECTIVE

This study utilized ChatGPT, an artificial intelligence program based on large language models, to explore controversial issues in pediatric inguinal hernia surgery and compare its responses with the guidelines of the European Association of Pediatric Surgeons (EUPSA).

METHODS

Six contentious issues raised by EUPSA were submitted to ChatGPT 4.0 for analysis, for which two independent responses were generated for each issue. These generated answers were subsequently compared with systematic reviews and guidelines. To ensure content accuracy and reliability, a content analysis was conducted, and expert evaluations were solicited for validation. Content analysis evaluated the consistency or discrepancy between ChatGPT 4.0's responses and the guidelines. An expert scoring method assess the quality, reliability, and applicability of responses. The TF-IDF model tested the stability and consistency of the two responses.

RESULTS

The responses generated by ChatGPT 4.0 were mostly consistent with the guidelines. However, some differences and contradictions were noted. The average quality score was 3.33, reliability score was 2.75, and applicability score was 3.46 (out of 5). The average similarity between the two responses was 0.72 (out of 1), Content analysis and expert ratings yielded consistent conclusions, enhancing the credibility of our research.

CONCLUSION

ChatGPT can provide valuable responses to clinical questions, but it has limitations and requires further improvement. It is recommended to combine ChatGPT with other reliable data sources to improve clinical practice and decision-making.

Academic clinician frontline-worker wellbeing and resilience during the COVID-19 pandemic experience: Were there gender differences?

Prior research suggests COVID-19 has amplified stress on Academic Clinician Frontline-Workers (ACFW). The aim of this paper is: (1) to better understand the experiences of ACFW during the COVID-19 pandemic including their mental-emotional wellbeing, academic productivity, clinical experiences, and (2) to examine any gender differences. A cross-sectional survey was administered to University of Minnesota/M Health Fairview systems' faculty February-June 2021. Of the 291 respondents, 156 were clinicians, with 91 (58 %) identifying as Frontline-Workers (ACFW). Faculty wellbeing was assessed using validated measures in addition to measures of productivity and sociodemographics. For example, ACFW reported a higher Work-Family Conflict (WFC) scores compared to non-ACFW (26.5 vs. 24.1, p = 0.057) but did not report higher Family-Work Conflict (FWC) scores (17.7 vs. 16.3, p = 0.302). Gender sub-analyses, revealed that women ACFW compared to men ACFW reported higher WFC scores (27.7 vs. 24.1, p = 0.021) and FWC (19.3 vs. 14.3, p = 0.004). Academically, ACFW reported submitting fewer grants and anticipated delays in promotion and tenure due to the COVID-19 (p = 0.035). Results suggest COVID-19 has exacerbated ACFW stress and gender inequities. Reports of anticipated delay in promotion for ACFW may pose a challenge for the long-term academic success of ACFW, especially women ACFW. In addition, women may experience higher FWC and WFC as compared to men. Schools of academic medicine should consider re-evaluating promotion/tenure processes and creating resources to support women ACFW as well as ACFW caregivers.

Inhibition of γδ T Cells Alleviates Blood-Brain Barrier in Cardiac Arrest and Cardiopulmonary Resuscitation in Mice

Ischemia/reperfusion (I/R) injury is the leading cause of death following cardiac arrest (CA) and cardiopulmonary resuscitation (CPR). γδT cells are suggested to aggravate blood-brain barrier (BBB) injury in various pathological processes. We herein investigate the effects of γδT cells inhibitor (UC7-13D5) against I/R injury post-CA/CPR. C57BL/6 mice were subjected to CA through injection of KCL (70 μL of 0.5 mol/L) and cessation of mechanical ventilation followed by CPR. Flow cytometry was performed to measure the proportion of CD3-positive cells after intraperitoneal injection of 200 μg UC7-13D5 at 6 h, 24 h, and 48 h post-resuscitation into mice. Neurological scores and modified neurological severity scores were assessed to examine neurological functions. Brain edema was estimated via brain water content measurements. Immunohistochemistry of caspase-3 and immunofluorescence staining of claudin-1, ZO-1 and CD31 were performed to detect neuronal apoptosis, BBB integrity and angiogenesis. Microvascular morphology in the cortical area was assessed via H&E staining. Oxidative stress was determined by measuring malondialdehyde, myeloperoxidase, xanthine oxidase, superoxide dismutase, and glutathione peroxidase activities. Western blotting was performed to measure the protein levels of Nuclear factor-E2-related factor 2 (Nrf2) and Heme oxygenase-1 (HO-1). UC7-13D5 effectively depleted γδT cells. Inhibition of γδT cells improved neurological deficits and reduced brain edema post-CA/CPR. γδT cells depletion attenuated neuronal apoptosis, BBB disruption and oxidative stress and promoted angiogenesis following CA/CPR. Inhibition of γδT cells facilitated the activation of the Nrf2/HO-1 pathway in CA/CPR-induced mice. Inhibition of γδT cells alleviates neurological deficits and cerebral edema in mice with CA/CPR by inhibiting neuronal apoptosis, BBB disruption and oxidative stress, and promoting angiogenesis via activation of the Nrf2/HO-1 pathway.

Evaluating the zoonotic potential of RNA viromes of rodents provides new insight into rodent-borne zoonotic pathogens in Guangdong, China

Emerging and re-emerging infectious diseases have been on the rise, with a significant proportion being zoonotic. Rodents, as the natural reservoirs of numerous diverse zoonotic viruses, pose a substantial threat to human health. To investigate the diversity of known and unknown viruses harbored by rodents in Guangdong (southern province of China), we conducted a comprehensive analysis of viral genomes through metagenomic sequencing of organs from 194 rodents. Our analysis yielded 2163 viral contigs that were assigned to 25 families known to infect a wide range of hosts, including vertebrates, invertebrates, amoebas, and plants. The viral compositions vary considerably among different organs, but not in rodent species. We also assessed and prioritized zoonotic potential of those detected viruses. Ninety-two viral species that are either known to infect vertebrates and invertebrates or only vertebrates were identified, among which 21 are considered high-risk to humans. The high-risk viruses included members of the Hantavirus, Picobirnaviruses, Astroviruses and Pestivirus. The phylogenetic trees of four zoonotic viruses revealed features of novel viral genomes that seem to fit evolutionarily into a zone of viruses that potentially pose a risk of transmission to humans. Recognizing that zoonotic diseases are a One Health issue, we approached the problem of identifying the zoonotic risk from rodent-transmitted disease in the Guangdong province by performing next-generation sequencing to look for potentially zoonotic viruses in these animals.

Fabrication of Dimples by Jet-ECM of Zr-Based Bulk Metallic Glasses with NaCl-Ethylene Glycol Electrolyte

Zr-based bulk metallic glasses (BMGs) possess unique mechanical and biochemical properties, which have been widely noticed. Jet electrochemical machining (jet-ECM), characterized by a high-speed jet, is a non-contact subtractive method with a high resolution and a high material removal rate (MRR). Past work on the electropolishing of Zr-based BMGs has indicated the feasibility of the NaCl-Ethylene Glycol (EG) electrolyte. In this research, the jet-ECM of Zr-based BMGs in the NaCl-EG electrolyte was studied to explore the dissolving mechanisms and surface integrity according to the voltage, pulse-on time and effective voltage time. The diameter, depth and surface morphologies of dimples were evaluated. The results showed that using this alcohol-based electrolyte led to a desirable surface morphology. The diameter and depth of the dimples varied with the voltage and the effective voltage time in a significantly positive proportional manner. Additionally, cases based on multiple parameter sets exhibited different stray corrosion severity. Afterward, machining performance can be enhanced in the next stage by tuning machining parameters to obtain microscale dimples with better quality.

Regular exercise attenuates alcoholic myopathy in zebrafish by modulating mitochondrial homeostasis

Alcoholic myopathy is caused by chronic consumption of alcohol (ethanol) and is characterized by weakness and atrophy of skeletal muscle. Regular exercise is one of the important ways to prevent or alleviate skeletal muscle myopathy. However, the beneficial effects and the exact mechanisms underlying regular exercise on alcohol myopathy remain unclear. In this study, a model of alcoholic myopathy was established using zebrafish soaked in 0.5% ethanol. Additionally, these zebrafish were intervened to swim for 8 weeks at an exercise intensity of 30% of the absolute critical swimming speed (Ucrit), aiming to explore the beneficial effects and underlying mechanisms of regular exercise on alcoholic myopathy. This study found that regular exercise inhibited protein degradation, improved locomotion ability, and increased muscle fiber cross-sectional area (CSA) in ethanol-treated zebrafish. In addition, regular exercise increases the functional activity of mitochondrial respiratory chain (MRC) complexes and upregulates the expression levels of MRC complexes. Regular exercise can also improve oxidative stress and mitochondrial dynamics in zebrafish skeletal muscle induced by ethanol. Additionally, regular exercise can activate mitochondrial biogenesis and inhibit mitochondrial unfolded protein response (UPRmt). Together, our results suggest regular exercise is an effective intervention strategy to improve mitochondrial homeostasis to attenuate alcoholic myopathy.

Radical-Induced Dissociation for Oligonucleotide Sequencing by TiO2/ZnAl-Layered Double Oxide-Assisted Laser Desorption/Ionization Mass Spectrometry

De novo sequencing of oligonucleotides remains challenging, especially for oligonucleotides with post-transcriptional or synthetic modifications. Mass spectrometry (MS) sequencing can reliably detect and locate all of the modification sites in oligonucleotides via m/z variance. However, current MS-based sequencing methods exhibit complex spectra and low ion abundance and usually require coupled instrumentation. Herein, we demonstrate a method of oligonucleotide sequencing using TiO2/ZnAl-layered double oxide (LDO)-assisted laser desorption/ionization (LDI)-MS based on radical-induced dissociation (RID). ·CH2OH radicals can be produced on the surface of a TiO2/ZnAl-LDO matrix via ultraviolet light, inducing an attack on the active site of the oligonucleotide phosphate skeleton to create typical "a-, a-B-, c·-, d-, w-, and y"-type fragments. Compared with the spectra obtained via collision-based methods, such as collision-induced dissociation and higher-energy collisional dissociation, the LDI-MS spectra based on RID exhibit single-charged signals, fewer types of fragments, and a lower proportion of unknown noise peaks. We demonstrate full sequence coverage for a 6-mer 2'-O-methyl-modified oligonucleotide and a 21-mer small interfering RNA and show that RID can sequence oligonucleotides with modifications. Importantly, the mechanism responsible for the RID of the oligonucleotide phosphate skeleton was investigated through offline experiments, demonstrating consistent results with density functional theory calculations.

Psychometric properties of the Sport Anxiety Scale-2 for Chinese adolescent athletes taking the National Sports College Entrance Examination

Background

This study aims to evaluate the psychometric properties of the Sport Anxiety Scale-2 (SAS-2) in Chinese adolescent sports exam candidates.

Methods

One day before the National Sports College Entrance Examination, 965 Chinese athletes rated the Chinese-language SAS-2. Confirmatory factor analysis was performed to test the three-factor structure. Factorial invariance was tested by comparing the configural invariance model to three more constrained models. Construct validity and reliability were determined.

Results

Fit indices meet the critical values: CFI = 0.953, TLI = 0.943, RMSEA = 0.048 [90% CI, 0.041-0.054], and SRMR = 0.042. All path factor loadings exceed 0.5. The changes in CFI and RMSEA across the configural, metric, scalar, and uniqueness invariance are within the critical values, demonstrating strict measurement invariance across gender, years of training, and type of sports. The average variance extracted of the worry sub-scale is above the cutoff criteria, and McDonald's omega coefficients are over 0.70. Significant correlations exist between the SAS-2, SCAT, and CSAI-2. Factor correlations are all below 0.8. The measurement also distinguishes the known gender effect, with females showing a probability of 58.6% higher anxiety levels. The intraclass correlation coefficient ranges from 0.706 to 0.801.

Conclusion

This study validated the Chinese-language SAS-2 in measuring competitive anxiety among Chinese adolescent athletes taking the National Sports College Entrance Examination. The development of the scale's applicability in China is discussed.

Identification and Automated Delineation of Radioresistant Biological Tumor Volume in Nasopharyngeal Carcinoma Based on Magnetic Resonance Imaging Radiomics

PURPOSE/OBJECTIVE(S)

Widespread use of intensity modulated radiotherapy (IMRT) has improved the tumor control rate of nasopharyngeal carcinoma (NPC). However, nearly 20% of the patients with local-advanced NPC would relapse after precise irradiation and 80% of the recurrent lesions occur within the high dose field, suggesting that there are radiation-resistant cancer cell subsets within the tumor. In this context, identification and contouring of radiation resistance region of NPC for dose escalation at primary IMRT could be advantageous. In this work, we proposed a two-step radiomics workflow to predict local relapse and the recurrent region of NPC before primary IMRT.

MATERIALS/METHODS

In this single-center, retrospective study, pre-treatment magnetic resonance (MR) sequences of T1-weighted imaging (T1-w) and contrast-enhanced T1-weighted imaging (CET1-w) were collected from 800 patients of newly diagnosed and non-metastatic NPC between April 2009 and December 2015. The primary gross tumor volume (GTVp) of all patients and the actual recurrent lesion (GTVr) of patients who suffered from local recurrence were manually contoured for further analysis. A two-step complete radiomics workflow was designed to predict tumor recurrence and segment the region. First, least absolute shrinkage and selection operator (LASSO) was utilized for radiomics features selection of GTVp and support vector machine (SVM) was adopted to predict the recurrence. If the model predicts a recurrence, then the workflow utilizes an improved 3D U-Net to segment the recurrent region. Area under receiver operating characteristic curve (ROC-AUC) was used to evaluate the performance of tumor recurrence prediction, and Dice similarity coefficient (DSC) was used to assess the consistence between the actual and predicted GTVr.

RESULTS

Of 800 NPC patients, 95 (11.9%) patients developed in-field local recurrence. For recurrence risk prediction, the SVM ensemble model (T1-w+CET1-w) was selected for further application with higher sensitivity. The average ROC-AUC, specificity, sensitivity of the SVM ensemble model in a 5-fold cross-validation and in the independent test set of 160 patients were 0.922, 0.922, 0.777 and 0.928, 0.915, 0.737, respectively. Moreover, for recurrent region segmentation, the multi-modality (T1-w+CET1-w) model was superior to the single-modality (T1-w or CET1-w) model. In an independent test set of 15 patients, the DSC, sensitivity and 95% Hausdorff Distance between actual and predicted GTVr was 0.549±0.176, 0.696±0.118 and 9.813±4.788 which was superior to 0.444±0.188, 0.497±0.218 and 12.047±5.361 of original 3D U-Net.

CONCLUSION

The proposed two-step radiomics workflow showed a good performance in predicting tumor recurrence of NPC. The predicted location of the recurrence lesion was all accurate, but there was still a certain difference between the volume of the automated delineated and actual GTVr, which needed to be further optimized to be used as biological tumor volume.

Automated Contouring of Cervical Lymph Nodes and Clinical Target Volumes for Nasopharyngeal Carcinoma Based on Deep Learning and Experience Constraints

PURPOSE/OBJECTIVE(S)

Application of artificial intelligence (AI) for automated contouring of tumor volumes and organs at risk (OARs) for radiotherapy of nasopharyngeal carcinoma (NPC) leads to improved contouring accuracy and efficiency. However, few studies have involved the automated contouring of gross tumor volume of cervical lymph nodes (GTVn) and clinical target volumes (CTVs). In this work, we proposed an AI automated contouring tool for GTVn and CTVs for radiotherapy of NPC on the plain scans of planning compute tomography (CT).

MATERIALS/METHODS

In this retrospective study, plain scan datasets of planning CT covering the nasopharynx and neck from 139 patients with NPC between March 2022 and December 2022 were collected and divided into training, validation, and testing cohorts of 95, 24, and 20 patients, respectively. Ground truth contours of primary gross tumor volume (GTVp), GTVn (divided into GTVn_L in left neck and GTVn_R in right neck), CTVs (including high risk CTV1 contains GTVp and low risk CTV2 contains GTVp and cervical nodal levels) and OARs were delineated and were defined by consensus of two experts. We first proposed a three-dimensional (3D) U-net using GTVp and OARs as experience constrains to guide the automated delineation of GTVn and CTVs. The average Dice similarity coefficient (DSC) and average surface distance (ASD) were used to quantify the performance of the AI tool. Next, five prospective patients were enrolled for clinical evaluation of our AI tool. DSC between automated contours and radiation oncologist-revised contours and time consuming of the revision were record.

RESULTS

Clinical characteristics of 139 retrospective and 5 prospective patients are list in Table 1. In the independent testing set of 20 patients, our AI tool showed high performance in GTVn and CTVs contouring when compared with the ground truth contours. The mean DSC were 0.73 ± 0.07, 0.74 ± 0.05, 0.93 ± 0.03, and 0.88 ± 0.03, and the mean ASD were 1.01 ± 0.43 mm, 1.14 ± 0.61 mm, 0.51 ± 0.13 mm, 1.17 ± 0.43 mm for GTVn_L, GTVn_R, CTV1 and CTV2, respectively. In the five prospective patients, mean DSC were 0.74 ± 0.07, 0.74 ± 0.10, 0.95 ± 0.01 and 0.89 ± 0.04, respectively. The median time consuming for GTVn and CTVs revision was 2minutes and 10 seconds (range, 1 minutes to 3 minutes).

CONCLUSION

The proposed AI tool integrating clinical experience as constrains showed high accuracy for contouring GTVn and CTVs of NPC. With the assistance of AI contours, contouring efficiency could be probably increased, which is promising in online adaptive radiotherapy of NPC.

An MRI-based machine learning radiomics can predict short-term response to neoadjuvant chemotherapy in patients with cervical squamous cell carcinoma: A multicenter study

BACKGROUND AND PURPOSE

Neoadjuvant chemotherapy (NACT) has become an essential component of the comprehensive treatment of cervical squamous cell carcinoma (CSCC). However, not all patients respond to chemotherapy due to individual differences in sensitivity and tolerance to chemotherapy drugs. Therefore, accurately predicting the sensitivity of CSCC patients to NACT was vital for individual chemotherapy. This study aims to construct a machine learning radiomics model based on magnetic resonance imaging (MRI) to assess its efficacy in predicting NACT susceptibility among CSCC patients.

METHODS

This study included 234 patients with CSCC from two hospitals, who were divided into a training set (n = 180), a testing set (n = 20), and an external validation set (n = 34). Manual radiomic features were extracted from transverse section MRI images, and feature selection was performed using the recursive feature elimination (RFE) method. A prediction model was then generated using three machine learning algorithms, namely logistic regression, random forest, and support vector machines (SVM), for predicting NACT susceptibility. The model's performance was assessed based on the area under the receiver operating characteristic curve (AUC), accuracy, and sensitivity.

RESULTS

The SVM approach achieves the highest scores on both the testing set and the external validation set. In the testing set and external validation set, the AUC of the model was 0.88 and 0.764, and the accuracy was 0.90 and 0.853, the sensitivity was 0.93 and 0.962, respectively.

CONCLUSIONS

Machine learning radiomics models based on MRI images have achieved satisfactory performance in predicting the sensitivity of NACT in CSCC patients with high accuracy and robustness, which has great significance for the treatment and personalized medicine of CSCC patients.

The axial and sagittal CT values of the 7th thoracic vertebrae in screening for osteoporosis and osteopenia

AIM

To evaluate the difference in computed tomography (CT) attenuation value of different planes of the 7th thoracic vertebra and investigate the efficacy of axial and sagittal vertebral CT measurements in predicting osteoporosis.

MATERIALS AND METHODS

Patients who underwent routine chest CT and dual-energy X-ray absorptiometry (DXA) within 1 month were included in this retrospective study. The CT attenuation values of different planes were compared. Logistic regression and receiver operating characteristic (ROC) were used to analyse the difference of each plane in the diagnosis of osteoporosis.

RESULTS

The study included 1,338 patients (mean age of 61.9±11.9; 54% female). The CT attenuation values decreased successively in the normal group, osteopenia group, and osteoporosis group. The paired t-test results showed that the mid-axial measurements were greater than mid-sagittal measurements, with a mean difference of 9 HU, the difference was statistically significant (p<0.001, 95% confidence interval [CI] = 7.8-10.1). For each one-unit reduction in mid-sagittal CT attenuation value, the risk of osteopenia or osteoporosis increased by 3.6%. To distinguish osteoporosis from non-osteoporosis (osteopenia + normal), the sensitivity was 90% and the specificity was 52.4% at the mid-sagittal threshold of 113.7 HU.

CONCLUSIONS

The CT attenuation values of mid-sagittal plane have higher diagnostic efficacy than axial planes in predicting osteoporosis. For patients with a sagittal CT attenuation value of <113.7 HU in the T7, further DXA examination is warranted.

Aggregation kinetics of green tea nanoparticles: Effects of pH, metal ions, and temperature

Colloidal nanoparticles in tea infusion are the link connecting micromolecular mechanism and macro-aggregation process of tea cream formation. In order to elucidate, the kinetics mechanism of green tea nanoparticles (gTNPs) aggregation, zeta-potentials, total average aggregation (TAA) rates, and critical coagulation concentration (CCC) in the presence of various pH and metal ions were investigated. Additionally, the effect of temperature on gTNPs aggregation was further explored. The results revealed that the TAA rate of gTNPs increased with decreasing pH values, the CCC of gTNPs increased in the order Mg2+  ≈ Ca2+  < Na+  ≈ K+ . The reason was that different positive ions changed the surface electric field strength of gTNPs to a different extent. Furthermore, it was indicated that low temperature could promote gTNPs aggregation in indirect way. Low temperature promoted the binding of epigallocatechin gallate (EGCG) and caffeine, and the combination between gTNPs and EGCG-caffeine complexes weakened the stability of gTNPs resulting from reduction in electrostatic repulsion. PRACTICAL APPLICATION: Tea is a popular beverage all over the world. This research revealed the mechanism of green tea nanoparticles aggregation and laid a theoretical foundation for the regulation of tea cream formation in tea beverage.

Molecular subtypes based on N6-methyladenosine RNA methylation demonstrate the heterogeneity of immune and biological functions in pediatric septic shock

Introduction

Septic shock in children is a highly heterogeneous syndrome involving different immune states and biological processes. We used a bioinformatics approach to explore the relationship between N6-methyladenosine (m6A) methylation and septic shock in children.

Methods

A gene expression dataset including information on 98 children with septic shock was selected. To construct and evaluate a risk prediction model, machine learning was used to screen marker m6A regulators. Based on differentially expressed m6A regulators, molecular subtypes for paediatric septic shock were constructed. Subsequently, the differences in the m6Ascore, heterogeneity of immune cell infiltration, and heterogeneity of biological functions between the different subtypes were analyzed. Finally, real-time quantitative PCR (RT-qPCR) was performed to validate the expression of the marker m6A regulators.

Results

Fifteen differentially expressed m6A regulators were identified. Six marker m6A regulators, including LRPPRC, ELAVL1, RBM15, CBLL1, FTO, and RBM15B, were screened using the random forest method. The risk prediction model for paediatric septic shock constructed using m6A markers had strong consistency and high clinical practicability. Two subtypes of paediatric septic shock have been identified based on the differential expression pattern of m6A regulators. Significant differences were observed in RNA epigenetics, immune statuses, and biological processes between the two m6A subtypes. Differentially expressed genes between the two subtypes were enriched in cell number homeostasis, redox responses, and innate immune system responses. Finally, the six marker m6A regulators were verified in additional samples.

Conclusions

Based on the heterogeneity of m6A methylation-regulated genes, two different subtypes of septic shock in children with different RNA epigenetics, immune statuses, and biological processes were identified, revealing the heterogeneity of the disease largely attributable to differential m6A methylation. The findings will help explore and establish appropriate individualized treatments.

Oncometabolite D-2-hydroxyglutarate-dependent metabolic reprogramming induces skeletal muscle atrophy during cancer cachexia

Cancer cachexia is characterized by weight loss and skeletal muscle wasting. Based on the up-regulation of catabolism and down-regulation of anabolism, here we showed genetic mutation-mediated metabolic reprogramming in the progression of cancer cachexia by screening for metabolites and investigating their direct effect on muscle atrophy. Treatment with 93 μM D-2-hydroxyglutarate (D2HG) resulted in reduced myotube width and increased expression of E3 ubiquitin ligases. Isocitrate Dehydrogenase 1 (IDH1) mutant patients had higher D2HG than non-mutant patients. In the in vivo murine cancer cachexia model, mutant IDH1 in CT26 cancer cells accelerated cachexia progression and worsened overall survival. Transcriptomics and metabolomics revealed a distinct D2HG-induced metabolic imbalance. Treatment with the IDH1 inhibitor ivosidenib delayed the progression of cancer cachexia in murine GL261 glioma model and CT26 colorectal carcinoma models. These data demonstrate the contribution of IDH1 mutation mediated D2HG accumulation to the progression of cancer cachexia and highlight the individualized treatment of IDH1 mutation associated cancer cachexia.