DoseDiff: Distance-aware Diffusion Model for Dose Prediction in Radiotherapy.

Treatment planning, which is a critical component of the radiotherapy workflow, is typically carried out by a medical physicist in a time-consuming trial-and-error manner. Previous studies have proposed knowledge-based or deep-learning-based methods for predicting dose distribution maps to assist medical physicists in improving the efficiency of treatment planning. However, these dose prediction methods usually fail to effectively utilize distance information between surrounding tissues and targets or organs-at-risk (OARs). Moreover, they are poor at maintaining the distribution characteristics of ray paths in the predicted dose distribution maps, resulting in a loss of valuable information. In this paper, we propose a distance-aware diffusion model (DoseDiff) for precise prediction of dose distribution. We define dose prediction as a sequence of denoising steps, wherein the predicted dose distribution map is generated with the conditions of the computed tomography (CT) image and signed distance maps (SDMs). The SDMs are obtained by distance transformation from the masks of targets or OARs, which provide the distance from each pixel in the image to the outline of the targets or OARs. We further propose a multi-encoder and multi-scale fusion network (MMFNet) that incorporates multi-scale and transformer-based fusion modules to enhance information fusion between the CT image and SDMs at the feature level. We evaluate our model on two in-house datasets and a public dataset, respectively. The results demonstrate that our DoseDiff method outperforms state-of-the-art dose prediction methods in terms of both quantitative performance and visual quality.

A One-Two Punch Strategy for Diabetic Wound Management Based on an Antibiotic-Hybrid Biomineralized Iron Sulfide Nanoparticle.

Bacterial infection and immune imbalance are the primary culprits behind chronic wounds in individuals with diabetes, impeding the progression of damaged tissues towards normal healing. To achieve a harmonious balance between pro- and anti-inflammation within these infected areas, herein, we propose a one-two punch strategy for on-demand therapy of diabetes-infected wounds, utilizing an azithromycin (AZM)-hybrid nanocomposite termed GOx@FexSy/AZM. During the infective stage, the nanocomposite facilitates the production of ROS, coupled with the burst release of AZM and H2S gas, effectively dismantling biofilms and achieving rapid sterilization. Subsequently, the hyperinflammatory response induced by antibiosis is significantly mitigated through the synergistic action of tissue H2S and the prolonged half-life of AZM. These components inhibit the activity of pro-inflammatory transcription factors (AP-1 and NF-κB) within macrophages, thereby promoting the polarization of macrophages towards a reparative M2 phenotype and facilitating tissue remodeling. By catering to the diverse requirements of wound healing at different stages, this nanocomposite accelerates a sensible transition from inflammation to the reparative phase. In summary, this one-two punch strategy gives an instructive instance for procedural treatment of diabetes wound infection. STATEMENT OF SIGNIFICANCE: The treatment of diabetic wound infection presents two major challenges: the diminished antibacterial efficacy arising from biofilm formation and bacterial resistance, as well as the inadequate transition of the wound microenvironment from pro-inflammatory to anti-inflammatory states after bacterial clearance. In this work, a biomineralized iron sulfide nanocomposite was prepared to mediate cascade catalytic (ROS storm) / antibiotic (AZM) / gas (H2S) triple-synergetic antibacterial therapy during the initial stage of bacterial infection, achieving the goal of rapid bactericidal effect; Subsequently, the residual H2S and long half-life AZM would inhibit the key pro-inflammatory transcription factors and promote the macrophages polarization to reparative M2, which effectively mediated tissue repair after hyperinflammatory reactions, leading to orderly treatment of hyperglycemic infected wounds.

The effects of role stressors and smartphone interactions on delivery riders' unsafe behaviors during the delivery process in China.

Objectives. Although some studies have shown role stressors can lead to unsafe behaviors, it is unclear how role stressors induce delivery riders' unsafe behaviors. We found that delivery riders suffered from tremendous role stressors during the delivery process and had to conduct frequent smartphone interactions. This study aimed to explore the effects of role stressors and smartphone interactions on delivery riders' unsafe behaviors. Methods. First, a questionnaire survey (N = 326) was used to collect data, and correlation and regression analyses were conducted to explore the relationship between role stressors, smartphone interaction frequency and delivery riders' unsafe behaviors. Second, a scenario survey (N = 35) was conducted, and comparative analysis was used to further explore how smartphone interactions affect delivery riders' unsafe behaviors. Results. The questionnaire survey revealed that role stressors, smartphone interaction frequency and delivery riders' unsafe behaviors were positively correlated. In addition, the role stressors forced delivery riders to conduct necessary and unnecessary smartphone interactions. The scenario survey found that smartphone interactions reduced delivery riders' motion speed and motion ability, and increased their psychology, so they had a risk-taking mentality, which led to an increase in unsafe behaviors.

The mitochondrial genome of Monoserius pennarius (Linnaeus, 1758) from the East China Sea.

The species Monoserius pennarius (Linnaeus, 1758), is particularly abundant in the tropical Indo-West Pacific east of Sri Lanka, yet very limited genetic information exists for this species. Here, we report the assembled-linear mitochondrial genome of M. pennarius collected from the East China Sea. The 15,197 bp mitogenome contains 13 protein-coding genes (PCGs), two tRNA genes, and two rRNA genes. Notably, the gene order in this mitogenome differs from that of other hydrozoans within the same taxonomic order. Phylogenetic analysis, based on 13 concatenated mitochondrial PCGs, recovered M. pennarius as a sister of Nemalecium lighti (Hargitt, 1924), outside the other Leptothecata hydrozoans, suggesting paraphyly of Leptothecata. The mitogenome of M. pennarius, serving as the first publicly available for the family Aglaopheniidae, holds foreseeable value for investigating Leptothecata evolution.

Characterizing the pathogenicity and mycotoxin production capacity of Fusarium spp. causing root rot of Angelica sinensis in China.

Root rot is a very destructive soil-borne disease, which severely affects the quality and yield of Angelica sinensis in major planting areas of Gansu Province, China. Twelve Fusarium strains were identified from root rot tissue and infected soil in the field, by comparing each isolate strain internal transcriptional spacer, translation elongation factor 1-α sequence and RNA polymerase second largest subunit gene (RPB2) with the sequences of known fungal species in the NCBI database. Of these isolates, four were F. acuminatum, followed by three F. solani, two F. oxysporum, and one each of F. equiseti, F. redolens, and F. avenaceum. Under greenhouse conditions, pathogenicity testing experiment was carried out using five strains: two F. acuminatum, one F. solani, one F. oxysporum, and one F. equiseti. Among them, the incidence of F. acuminatum-induced root rot on A. sinensis was 100%; hence, it was the most aggressive. Liquid chromatography was used to show that F. acuminatum was capable of producing neosolaniol (NEO), deoxynivalenol (DON), and T-2 toxins. Of these, the level of NEO produced by F. acuminatum was high, compared with the other two toxins. By isolating Fusarium spp. and characterizing their toxin-producing capacity, this work provides a new information for effectively preventing and controlling A. sinensis root rot in the field, as well as improving the quality of its medicinal materials. Keywords: Angelica sinensis, Fusarium spp., mycotoxins, pathogenicity tests, root rot disease.

Epidural ropivacaine versus bupivacaine for cesarean sections: a system review and meta-analysis.

INTRODUCTION: It is still no consensus on the use of ropivacaine or bupivacaine in epidural anesthesia for cesarean section (CS), because their anesthetic potency and relative complications remains controversial. This system review and meta-analysis aimed to compare the efficacy of epidural ropivacaine and bupivacaine for elective CSs and investigate relative complications for parturients and neonates. METHODS: We searched PubMed, MEDLINE, Embase, Cochrane Library, Science-Direct, and Google Scholar to June 30, 2023 for randomized controlled trials (RCTs), which compared epidural ropivacaine with bupivacaine for elective CSs. The success rate of epidural anesthesia (EA) was primary outcome. The secondary outcomes included onset times of sensory block, maternal side effects, neonatal Apgar scores and umbilical artery pH. RESULTS: We analyzed 8 RCTs with 532 parturients. 0.75% ropivacaine is associated with a shorter onset time of sensory block than 0.5% bupivacaine (SMD = -0.43, 95% CI: -0.70 to -0.17; p = .001). 0.5% ropivacaine resulted in a reduced nausea than 0.5% bupivacaine (RR = 0.49, 95% CI: 0.28 to 0.83; p = .008). In addition, there were no significant difference between ropivacaine and bupivacaine groups in terms of success rate of epidural anesthesia, maternal side effects (hypotension, bradycardia, shivering), and neonatal Apgar scores and umbilical artery pH. CONCLUSIONS: The findings suggest that there were no significant difference between epidural ropivacaine and bupivacaine for elective CSs in terms of the success rate (85.9% vs. 83.5), maternal side effects (hypotension, bradycardia, shivering), and neonatal Apgar scores and umbilical artery pH. But compared with 0.5% bupivacaine, epidural 0.75% ropivacaine was mildly effective for reducing onset time of sensory block and 0.5% ropivacaine reduced the incidence of maternal nausea.

Attention-Gated Deep-Learning-Based Automatic Digitization of Interstitial Needles in High-Dose-Rate Brachytherapy for Cervical Cancer.

Purpose: Deep learning can be used to automatically digitize interstitial needles in high-dose-rate (HDR) brachytherapy for patients with cervical cancer. The aim of this study was to design a novel attention-gated deep-learning model, which may further improve the accuracy of and better differentiate needles. Methods and Materials: Seventeen patients with cervical cancer with 56 computed tomography-based interstitial HDR brachytherapy plans from the local hospital were retrospectively chosen with the local institutional review board's approval. Among them, 50 plans were randomly selected as the training set and the rest as the validation set. Spatial and channel attention gates (AGs) were added to 3-dimensional convolutional neural networks (CNNs) to highlight needle features and suppress irrelevant regions; this was supposed to facilitate convergence and improve accuracy of automatic needle digitization. Subsequently, the automatically digitized needles were exported to the Oncentra treatment planning system (Elekta Solutions AB, Stockholm, Sweden) for dose evaluation. The geometric and dosimetric accuracy of automatic needle digitization was compared among 3 methods: (1) clinically approved plans with manual needle digitization (ground truth); (2) the conventional deep-learning (CNN) method; and (3) the attention-added deep-learning (CNN + AG) method, in terms of the Dice similarity coefficient (DSC), tip and shaft positioning errors, dose distribution in the high-risk clinical target volume (HR-CTV), organs at risk, and so on. Results: The attention-gated CNN model was superior to CNN without AGs, with a greater DSC (approximately 94% for CNN + AG vs 89% for CNN). The needle tip and shaft errors of the CNN + AG method (1.1 mm and 1.8 mm, respectively) were also much smaller than those of the CNN method (2.0 mm and 3.3 mm, respectively). Finally, the dose difference for the HR-CTV D90 using the CNN + AG method was much more accurate than that using CNN (0.4% and 1.7%, respectively). Conclusions: The attention-added deep-learning model was successfully implemented for automatic needle digitization in HDR brachytherapy, with clinically acceptable geometric and dosimetric accuracy. Compared with conventional deep-learning neural networks, attention-gated deep learning may have superior performance and great clinical potential.

First Report of Powdery Mildew Caused by Erysiphe cruciferarum on Orychophragmus violaceus in China.

Orychophragmus violaceus is an annual or perennial herb in the Brassicaceae family. It is widely planted in China and used as an ornamental and green manure plant (Luo et al. 2022). In September 2022, a survey conducted in a 600 m2 garden in Lanzhou (36°06'N, 103°43'E) found that over 70% of O. violaceus plants were infected with powdery mildew, with 80% of the leaf area on the upper surface of infected leaves was infected. The white colonies on the upper surface of the leaves gradually expanded, thickened, and spread to cover the stem surface. In severe cases, entire foliage withered and the plants died. Fungal structures were taken from the leaves with adhesive tape and placed in sterile water for microscopic observation. The conidiophores were upright, cylindrical, composed of 3 to 4 cells, and measured 92.3 ± 12.9 × 9.2 ± 0.6 µm (n=30). Conidial pedicels had 21.6 ± 3.4 µm (n=50) long cylindrical podocytes. Monoconidia were cylindrical or oval in shape, 32.9 ± 6.1 µm long and 15.1 ± 2.1 µm wide (n=80). Conidia lacked an obvious cellulose body. The bud tubes formed from the end of conidia, and papillary appressoria developed on the epiphytic mycelia. Based on these morphological characteristics, the pathogen was initially identified as Erysiphe cruciferarum (Braun et al. 2012). To validate the identity, the internal transcribed spacer (ITS) region of an isolate EYL was amplified by PCR and sequenced using both ITS1/ITS4 and ITS5/PM6 primers (Takamatsu et al. 2001). The resulting sequences were deposited at GenBank (accession nos: OR437967 and OR437969). The ITS sequence of the isolate EYL (OR437967) is 99% (451/453) identical to E. cruciferarum (KP730001) on Brassica napus in China and that of the isolate EYL (OR437969) is 100% (509/509) identical to E. cruciferarum (KM260718) on B. juncea in Vietnam. Pathogenicity experiments were performed on six-week-old plants with an average of 10 ± 0.8 leaves. In the inoculated group, five healthy plants were inoculated by gently pressing the upper surface of diseased leaves against the upper surface of leaves of healthy plants for about 5 to 10 seconds. In the control group, the leaves of five healthy plants were treated with asymptomatic using the same method as described above. The plants were maintained in a greenhouse set at 25℃, 14-h photoperiod, and ≥ 70% humidity. After 13 days, all inoculated plants showed symptoms of powdery mildew, while the plants in the control group had no symptoms. The fungus on the inoculated plant was re-isolated and identified as E. cruciferarum based on its morphological characteristics and ITS sequence. Powdery mildew caused by E. cruciferarum has been reported on Cleome hassleriana in Italy and B. juncea in Australia (Garibaldi et al. 2009; Kaur et al. 2008). To our knowledge, this is the first time that powdery mildew caused by E. cruciferarum have been reported on O. violaceus in China. This disease poses a potential threat to the quality and yield of O. violaceus plants, which may warrant the development of preventative and management strategies in the future.

Functional Characterization of a Novel SLC4A4 Variant and Uniparental Isodisomy in Proximal Renal Tubular Acidosis Patient.

SLC4A4 variants are the etiologies of inherited proximal renal tubular acidosis (pRTA), which results in metabolic acidosis, hypokalemia, glaucoma, band keratopathy, and cataract. This study aims to characterize SLC4A4 variant and uniparental isodisomy of chromosome 4 in a patient, and analyse the functional characterization of SLC4A4 variants. This study analyzed renal tubular acidosis disease genes by whole exome sequencing (WES). H3M2 algorithm was used to analyze the run of homozygosity region in chromosomal regions in trio-WES data. The pathogenicity analysis of variants was performed using bioinformatics tools. Additionally, protein stability was analyzed by cycloheximide chase assay. Whole-cell patch clamping was used to examine the electrophysiological properties of NBCe1-A. A novel homozygous SLC4A4 variant was identified in the patient: a missense variant c.496C > T, p. Arg166Trp (NM_003759.4). But the father was heterozygous variant carrier, and the mother did not detect the variant. The H3M2 and UPDio algorithm revealed paternal uniparental isodisomy on chromosome 4 in the patient. SIFT, Poly Phen-2, FATHMM and Mutant Taster showed that the variant might be pathogenic. The tertiary structure analysis showed that the variant could cause structural damage to NBCe1 protein. Foldx results showed that the protein stability of the variant was slightly reduced. Cycloheximide chase assay demonstrated that the variant affects protein stability. The result of electrophysiological studies showed that the variant altered Na+/HCO3- cotransport activity of protein. In conclusion, the study is the first to report a pRTA patient with Arg166Trp variant with UPiD (4) pat and analyze the function of Arg166Trp variant.

Theoretical Kinetic Study on Hydrogen Abstraction Reactions from n-Pentane by NO2.

The interaction of fuel with NOx chemistry is important for the construction of the reaction mechanism and engine application. In this work, the reaction pathways of nC5H12 + NO2 were studied by high-level electronic structure calculations (DLPNO-CCSD(T)-F12/cc-pVTZ-F12//B2PLYPD3/cc-pVTZ). The rate constants were calculated by using the multistructural canonical transition-state theory with the Eckart tunneling method (TST/MS-T/ET). The studied condition is in a wide temperature range of 298-2400 K. The influence of MS-T anharmonicity and tunneling effect will be clarified for these site-specific H-abstraction pathways. The result reflects the large deviation introduced by the treatment of MS-T anharmonicity, especially at a high temperature. For the same type of reactions, the rate constants of H-abstraction both occurring at the secondary carbon are not almost identical. The branching ratios show that abstraction from the secondary site forming cis-HONO (R2c) contributes 36-78% to nC5H12 consumption in the temperature range of 298-2400 K. The current results show that the multistructural torsional anharmonicity has a crucial influence on the accurate estimation of branching ratios.

Generalisation of radiotherapy dose calculation for Monte Carlo algorithm combined with 3D Swin-Unet: a multi-institutional IMRT evaluation.

Objective.Accurate dose calculations are essential prerequisites for precise radiotherapy. The integration of deep learning into dosimetry could consider computational accuracy and efficiency and has potential applicability to clinical dose calculation. The generalisation of a deep learning dose calculation method (hereinafter referred to as TERMA-Monte Carlo network, T-MC net) was evaluated in clinical practice using intensity-modulated radiotherapy (IMRT) plans for various human body regions and multiple institutions, with the Monte Carlo (MC) algorithm serving as a benchmark.Approach. Sixty IMRT plans were selected from four institutions for testing the head and neck, chest and abdomen, and pelvis regions. Using the MC results as the benchmark, the T-MC net calculation results were used to perform three-dimensional dose distribution and dose-volume histogram (DVH) comparisons of the entire body, planning target volume (PTV) and organs at risk (OARs), respectively, and calculate the mean ±95% confidence interval of gamma pass rate (GPR), percentage of agreement (PA) and dose difference ratio (DDR) of dose indices D95, D50, and D5.Main results. For the entire body, the GPRs of 3%/3 mm, 2%/2 mm, 2%/1 mm, and the PA were 99.62 ± 0.32%, 98.50 ± 1.09%, 95.60 ± 2.90% and 97.80 ± 1.12%, respectively. For the PTV, the GPRs of 3%/3 mm, 2%/2 mm, 2%/1 mm and the PA were 98.90 ± 1.00%, 95.78 ± 2.83%, 92.23 ± 4.74% and 98.93 ± 0.62%, respectively. The absolute value of average DDR was less than 1.4%.Significance. We proposed a general dose calculation framework based on deep learning, using the MC algorithm as a benchmark, performing a generalisation test for IMRT treatment plans across multiple institutions. The framework provides high computational speed while maintaining the accuracy of MC and may become an effective dose algorithm engine in treatment planning, adaptive radiotherapy, and dose verification.

Preliminary study on dosimetry characteristics of a novel cylindrical dose verification system.

OBJECTIVE: To develop a novel ionization chamber array dosimetry system, study its dosimetry characteristics, and perform preliminary tests for plan dose verification. METHODS: The dosimetry characteristics of this new array were tested, including short-term and long-term reproducibility, dose linearity, dose rate dependence, field size dependence, and angular dependence. The open field and MLC field plans were designed for dose testing. Randomly select 30 patient treatment plans (10 intensity-modulated radiation therapy [IMRT] plans and 20 volumetric modulated arc therapy [VMAT] plans) that have undergone dose verification using Portal Dosimetry to perform verification measurement and evaluate dose verification test results. RESULTS: The dosimetry characteristics of the arrays all performed well. The gamma passing rates (3%/2 mm) were more than 96% for the combined open field and MLC field plans. The average gamma pass rates were (99.54 ± 0.58)% and (96.70 ± 3.41)% for the 10 IMRT plans and (99.32 ± 0.89)% and (94.91 ± 6.01)% for the 20 VMAT plans at the 3%/2 mm and 2%/2 mm criteria, respectively, which is similar to the Portal Dosimetry's measurement results. CONCLUSIONS: This novel ionization chamber array demonstrates good dosimetry characteristics and is suitable for clinical IMRT and VMAT plan verifications.

Chiral lanthanide-silver(I) cluster-based metal-organic frameworks exhibiting solvent stability, and tunable photoluminescence.

Due to the lack of effective synthetic strategies, the preparation of chemically stable chiral Ag(I) cluster-based materials for assembly remains challenging. Here, we have developed an approach to synthesize three pairs of chiral Ln-Ag(I) cluster-based metal-organic frameworks (MOFs) named l-LnAg5-3D (Ln = Gd for 1-L, Eu for 2-L, and Tb for 3-L) and d-LnAg5-3D (Ln = Gd for 1-D, Eu for 2-D, and Tb for 3-D) by employing a chiral Ag(I) cluster ({Ag5S6}) as the node and Ln3+ ion as the inorganic linker. Structural analysis revealed that the chiral ligands induced chirality through the entire structure, resulting in a chiral helix arrangement of the C3-symmetric chiral {Ag5S6} nodes and Ln3+ ions. These compounds showed high solvent stability in various polar organic solvents. The solid-state circular dichroism (CD) spectra of compounds l-LnAg5-3D and d-LnAg5-3D exhibited obvious mirror symmetrical peaks. The emission spectra in the solid state revealed that compound 1-L only exhibited the emission peak of {Ag5S6}, while compounds 2-L and 3-L exhibited overlapping peaks of Ln3+ and {Ag5S6} at different excitation wavelengths. This demonstrates the tunable photoluminescence from {Ag5S6} to Ln3+ by introducing different Ln3+ ions and manipulating the excitation wavelengths. The study underscores the enhanced stability of Ag(I) cluster-based MOFs achieved through the incorporation of Ln3+ ions and establishes chiral Ln-Ag(I) cluster-based MOFs as promising candidates for advanced materials with tunable photoluminescence.

Effect of mindfulness-based mind-body therapies in patients with non-specific low back pain-A network meta-analysis of randomized controlled trials.

Background/objectives: Although mindfulness-based mind-body therapy (MBMBT) is an effective non-surgical treatment for patients with non-specific low back pain (NLBP), the best MBMBT mode of treatment for NLBP patients has not been identified. Therefore, a network meta-analysis (NMA) was conducted to compare the effects of different MBMBTs in the treatment of NLBP patients. Methods: PubMed, EMBASE, Cochrane Central Register of Controlled Trials, and Web of Science databases were searched for randomized controlled trials (RCTs) applying MBMBT for the treatment of NLBP patients, with all of the searches ranging from the time of database creation to January 2023. After 2 researchers independently screened the literature, extracted information, and evaluated the risks of biases in the included studies, the data were analyzed by using Stata 16.0 software. Results: A total of 46 RCTs were included, including 3,886 NLBP patients and 9 MBMBT (Yoga, Ayurvedic Massage, Pilates, Craniosacral Therapy, Meditation, Meditation + Yoga, Qigong, Tai Chi, and Dance). The results of the NMA showed that Craniosacral Therapy [surface under the cumulative ranking (SUCRA): 99.2 and 99.5%] ranked the highest in terms of improving pain and disability, followed by Other Manipulations (SUCRA: 80.6 and 90.8%) and Pilates (SUCRA: 54.5 and 71.2%). In terms of improving physical health, Craniosacral Therapy (SUCRA: 100%) ranked the highest, followed by Pilates (SUCRA: 72.3%) and Meditation (SUCRA: 55.9%). In terms of improving mental health, Craniosacral Therapy (SUCRA: 100%) ranked the highest, followed by Meditation (SUCRA: 70.7%) and Pilates (SUCRA: 63.2%). However, in terms of improving pain, physical health, and mental health, Usual Care (SUCRA: 7.0, 14.2, and 11.8%, respectively) ranked lowest. Moreover, in terms of improving disability, Dance (SUCRA: 11.3%) ranked lowest. Conclusion: This NMA shows that Craniosacral Therapy may be the most effective MBMBT in treating NLBP patients and deserves to be promoted for clinical use. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, PROSPERO [CRD42023389369].

The porcine piRNA transcriptome response to Senecavirus a infection.

Introduction: Senecavirus A (SVA) belongs to the genus Senecavirus in the family Picornaviridae. PIWI-interacting RNAs (piRNAs) are a class of small Ribonucleic Acids (RNAs) that have been found in mammalian cells in recent years. However, the expression profile of piRNAs in the host during SVA infection and their roles are poorly understood. Methods: Here, we found the significant differential expression of 173 piRNAs in SVA-infected porcine kidney (PK-15) cells using RNA-seq and 10 significant differentially expressed (DE) piRNAs were further verified by qRT-PCR. Results: GO annotation analysis showed that metabolism, proliferation, and differentiation were significantly activated after SVA infection. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that significant DE piRNAs were mainly enriched in AMPK pathway, Rap1 pathway, circadian rhythm and VEGF pathway. It was suggested that piRNAs may regulated antiviral immunity, intracellular homeostasis, and tumor activities during SVA infection. In addition, we found that the expression levels of the major piRNA-generating genes BMAL1 and CRY1 were significantly downregulated after SVA infection. Discussion: This suggests that SVA may affect circadian rhythm and promote apoptosis by inhibiting the major piRNA-generating genes BMAL1 and CRY1. The piRNA transcriptome in PK-15 cells has never been reported before, and this study will further the understanding of the piRNA regulatory mechanisms underlying SVA infections.

Breath-Hold CBCT-Guided CBCT-to-CT Synthesis via Multimodal Unsupervised Representation Disentanglement Learning.

Adaptive radiation therapy (ART) aims to deliver radiotherapy accurately and precisely in the presence of anatomical changes, in which the synthesis of computed tomography (CT) from cone-beam CT (CBCT) is an important step. However, because of serious motion artifacts, CBCT-to-CT synthesis remains a challenging task for breast-cancer ART. Existing synthesis methods usually ignore motion artifacts, thereby limiting their performance on chest CBCT images. In this paper, we decompose CBCT-to-CT synthesis into artifact reduction and intensity correction, and we introduce breath-hold CBCT images to guide them. To achieve superior synthesis performance, we propose a multimodal unsupervised representation disentanglement (MURD) learning framework that disentangles the content, style, and artifact representations from CBCT and CT images in the latent space. MURD can synthesize different forms of images using the recombination of disentangled representations. Also, we propose a multipath consistency loss to improve structural consistency in synthesis and a multidomain generator to improve synthesis performance. Experiments on our breast-cancer dataset show that MURD achieves impressive performance with a mean absolute error of 55.23±9.94 HU, a structural similarity index measurement of 0.721±0.042, and a peak signal-to-noise ratio of 28.26±1.93 dB in synthetic CT. The results show that compared to state-of-the-art unsupervised synthesis methods, our method produces better synthetic CT images in terms of both accuracy and visual quality.

Berberine Alleviates Acute Lung Injury in Septic Mice by Modulating Treg/Th17 Homeostasis and Downregulating NF-κB Signaling.

Purpose: A common complication of sepsis is acute lung injury (ALI), which is associated with an acute onset, rapid disease changes, and high mortality. Regulatory T (Treg) and T helper 17 (Th17) cells comprise CD4+ T cell subsets, which strongly influence inflammation during ALI. In this study, we investigated the effect of berberine (BBR), an antioxidant, anti-inflammatory, and immunomodulatory drug, on the inflammatory response and immune state in mice with sepsis. Methods: A mouse model of cecal ligation and puncture (CLP) was established. The mice were intragastrically administered 50 mg/kg BBR. We used histological techniques to evaluate inflammatory tissue injury and flow cytometry for analyzing Treg/Th17 levels. We also assessed NF-κB signaling pathways by Western blotting assays and immunofluorescence staining. Enzyme-linked immunosorbent assay (ELISA) was performed to measure the content of cytokines. Results: Treatment with BBR considerably mitigated lung injury while improving survival, post-cecal ligation, and puncture (CLP). Treatment with BBR ameliorated pulmonary edema and hypoxemia in septic mice and inhibited the NF-κB signaling pathway. BBR also increased Treg cells and decreased Th17 proportions in the spleen and lung tissue of CLP-treated mice. Blocking Treg cells weakened the protective effect of BBR on sepsis-associated lung injury. Conclusion: Overall, these results suggested that BBR is a potential therapeutic agent for sepsis.

Effect of Cu loading on the performance and kinetics of Cu/SAPO-34 catalysts for selective catalytic reduction with NH3.

A series of X%Cu/SAPO-34 (X = 1.0, 2.0, 4.0 and 6.0) catalysts were prepared by ultrasonic impregnation method for selective catalytic reduction (SCR) of NOx with ammonia. The effect of different Cu loadings on the selective catalytic reduction of NO by molecular sieve catalysts was examined on a fixed-bed reactor. Catalyst physicochemical properties were characterized and analyzed using XRD, TEM, NH3-TPD, H2-TPR, and in situ DRIFTS. Catalysts were used in reaction kinetics studies from the perspective of transient and steady-state kinetics. Cu/SAPO-34 catalyst with 4% Cu loading had the best denitrification efficiency and wide activity window. Copper species were highly dispersed on the catalyst surface. Cu/SAPO-34 catalyst with 4% Cu loading had rich acidic sites and excellent redox performance. Cu/SAPO-34 catalysts with 4% Cu loading possess minimal activation energy and were lower than commercial catalysts. According to the results of in situ IR, transient and steady-state analysis, the Cu/SAPO-34 catalyst with 4% Cu loading in the NH3-SCR reaction process was mainly E-R mechanism, and there was L-H mechanism.

Automatic prediction model for online diaphragm motion tracking based on optical surface monitoring by machine learning.

Background: The aim of this study was to establish a correlation model between external surface motion and internal diaphragm apex movement using machine learning and to realize online automatic prediction of the diaphragm motion trajectory based on optical surface monitoring. Methods: The optical body surface parameters and kilovoltage (kV) X-ray fluoroscopic images of 7 liver tumor patients were captured synchronously for 50 seconds. The location of the diaphragm apex was manually delineated by a radiation oncologist and automatically detected with a convolutional network model in fluoroscopic images. The correlation model between the body surface parameters and the diaphragm apex of each patient was developed through linear regression (LR) based on synchronous datasets before radiotherapy. Model 1 (M1) was trained with data from the first 30 seconds of the datasets and tested with data from the following 20 seconds of the datasets in the first fraction to evaluate the intra-fractional prediction accuracy. Model 2 (M2) was trained with data from the first 30 seconds of the datasets in the next fraction. The motion trajectory of the diaphragm apex during the following 20 seconds in the next fraction was predicted with M1 and M2, respectively, to evaluate the inter-fractional prediction accuracy. The prediction errors of the 2 models were compared to analyze whether the correlation model needed to be re-established. Results: The average mean absolute error (MAE) and root mean square error (RMSE) using M1 trained with automatic detection location for the first fraction were 3.12±0.80 and 3.82±0.98 mm in the superior-inferior (SI) direction and 1.38±0.24 and 1.74±0.32 mm in the anterior-posterior (AP) direction, respectively. The average MAE and RMSE of M1 versus M2 in the AP direction were 2.63±0.71 versus 1.28±0.48 mm and 3.26±0.90 versus 1.61±0.60 mm, respectively. The average MAE and RMSE of M1 versus M2 in the SI direction were 5.84±1.22 versus 3.37±0.43 mm and 7.22±1.45 versus 4.07±0.54 mm, respectively. The prediction accuracy of M2 was significantly higher than that of M1. Conclusions: This study shows that it is feasible to use optical body surface information to automatically predict the diaphragm motion trajectory. At the same time, it is necessary to establish a new correlation model for the current fraction before each treatment.