Human-like intelligent automatic treatment planning of head and neck cancer radiation therapy.

Automatic treatment planning of radiation therapy (RT) is desired to ensure plan quality, improve planning efficiency, and reduce human errors. We have proposed an Intelligent Automatic Treatment Planning framework with a virtual treatment planner (VTP), an artificial intelligence robot built using deep reinforcement learning (DRL), autonomously operating a treatment planning system (TPS). This study extends our previous successes in relatively simple prostate cancer RT planning to head-and-neck (H&N) cancer, a more challenging context even for human planners due to multiple prescription levels, proximity of targets to critical organs, and tight dosimetric constraints. We integrated VTP with a real clinical TPS to establish a fully automated planning workflow guided by VTP. This integration allowed direct model training and evaluation using the clinical TPS. We designed the VTP network structure to approach the decision-making process in RT planning in a hierarchical manner that mirrors human planners. The VTP network was trained via the Q-learning framework. To assess the effectiveness of VTP, we conducted a prospective evaluation in the 2023 Planning Challenge organized by the American Association of Medical Dosimetrists (AAMD). We extended our evaluation to include 20 clinical H&N cancer patients, comparing the plans generated by VTP against their clinical plans. In the prospective evaluation for the AAMD Planning Challenge, VTP achieved a plan score of 139.08 in the initial phase evaluating plan quality, and 15 min of planning time with the first place ranking in the adaptive phase competing for planning efficiency while meeting all plan quality requirements. For clinical cases, VTP-generated plans achieved an average VTP score of 125.33±11.12, which outperformed the corresponding clinical plans with an average score of117.76±13.56. We successfully integrated VTP with the clinical TPS to achieve a fully automated treatment planning workflow. The compelling performance of VTP demonstrated its potential in automating H&N RT planning.

Predictive modeling for postoperative delirium in elderly patients with abdominal malignancies using synthetic minority oversampling technique.

BACKGROUND: Postoperative delirium, particularly prevalent in elderly patients after abdominal cancer surgery, presents significant challenges in clinical management. AIM: To develop a synthetic minority oversampling technique (SMOTE)-based model for predicting postoperative delirium in elderly abdominal cancer patients. METHODS: In this retrospective cohort study, we analyzed data from 611 elderly patients who underwent abdominal malignant tumor surgery at our hospital between September 2020 and October 2022. The incidence of postoperative delirium was recorded for 7 d post-surgery. Patients were divided into delirium and non-delirium groups based on the occurrence of postoperative delirium or not. A multivariate logistic regression model was used to identify risk factors and develop a predictive model for postoperative delirium. The SMOTE technique was applied to enhance the model by oversampling the delirium cases. The model's predictive accuracy was then validated. RESULTS: In our study involving 611 elderly patients with abdominal malignant tumors, multivariate logistic regression analysis identified significant risk factors for postoperative delirium. These included the Charlson comorbidity index, American Society of Anesthesiologists classification, history of cerebrovascular disease, surgical duration, perioperative blood transfusion, and postoperative pain score. The incidence rate of postoperative delirium in our study was 22.91%. The original predictive model (P1) exhibited an area under the receiver operating characteristic curve of 0.862. In comparison, the SMOTE-based logistic early warning model (P2), which utilized the SMOTE oversampling algorithm, showed a slightly lower but comparable area under the curve of 0.856, suggesting no significant difference in performance between the two predictive approaches. CONCLUSION: This study confirms that the SMOTE-enhanced predictive model for postoperative delirium in elderly abdominal tumor patients shows performance equivalent to that of traditional methods, effectively addressing data imbalance.

Clinical VMAT machine parameter optimization for localized prostate cancer using deep reinforcement learning.

BACKGROUND: Volumetric modulated arc therapy (VMAT) machine parameter optimization (MPO) remains computationally expensive and sensitive to input dose objectives creating challenges for manual and automatic planning. Reinforcement learning (RL) involves machine learning through extensive trial-and-error, demonstrating performance exceeding humans, and existing algorithms in several domains. PURPOSE: To develop and evaluate an RL approach for VMAT MPO for localized prostate cancer to rapidly and automatically generate deliverable VMAT plans for a clinical linear accelerator (linac) and compare resultant dosimetry to clinical plans. METHODS: We extended our previous RL approach to enable VMAT MPO of a 3D beam model for a clinical linac through a policy network. It accepts an input state describing the current control point and predicts continuous machine parameters for the next control point, which are used to update the input state, repeating until plan termination. RL training was conducted to minimize a dose-based cost function for prescription of 60 Gy in 20 fractions using CT scans and contours from 136 retrospective localized prostate cancer patients, 20 of which had existing plans used to initialize training. Data augmentation was employed to mitigate over-fitting, and parameter exploration was achieved using Gaussian perturbations. Following training, RL VMAT was applied to an independent cohort of 15 patients, and the resultant dosimetry was compared to clinical plans. We also combined the RL approach with our clinical treatment planning system (TPS) to automate final plan refinement, and creating the potential for manual review and edits as required for clinical use. RESULTS: RL training was conducted for 5000 iterations, producing 40 000 plans during exploration. Mean ± SD execution time to produce deliverable VMAT plans in the test cohort was 3.3 ± 0.5 s which were automatically refined in the TPS taking an additional 77.4 ± 5.8 s. When normalized to provide equivalent target coverage, the RL+TPS plans provided a similar mean ± SD overall maximum dose of 63.2 ± 0.6 Gy and a lower mean rectum dose of 17.4 ± 7.4 compared to 63.9 ± 1.5 Gy (p = 0.061) and 21.0 ± 6.0 (p = 0.024) for the clinical plans. CONCLUSIONS: An approach for VMAT MPO using RL for a clinical linac model was developed and applied to automatically generate deliverable plans for localized prostate cancer patients, and when combined with the clinical TPS shows potential to rapidly generate high-quality plans. The RL VMAT approach shows promise to discover advanced linac control policies through trial-and-error, and algorithm limitations and future directions are identified and discussed.

Detection of Novel BEST1 Variations in Autosomal Recessive Bestrophinopathy Using Third-generation Sequencing.

OBJECTIVE: Autosomal recessive bestrophinopathy (ARB), a retinal degenerative disease, is characterized by central visual loss, yellowish multifocal diffuse subretinal deposits, and a dramatic decrease in the light peak on electrooculogram. The potential pathogenic mechanism involves mutations in the BEST1 gene, which encodes Ca2+-activated Cl- channels in the retinal pigment epithelium (RPE), resulting in degeneration of RPE and photoreceptor. In this study, the complete clinical characteristics of two Chinese ARB families were summarized. METHODS: Pacific Biosciences (PacBio) single-molecule real-time (SMRT) sequencing was performed on the probands to screen for disease-causing gene mutations, and Sanger sequencing was applied to validate variants in the patients and their family members. RESULTS: Two novel mutations, c.202T>C (chr11:61722628, p.Y68H) and c.867+97G>A, in the BEST1 gene were identified in the two Chinese ARB families. The novel missense mutation BEST1 c.202T>C (p.Y68H) resulted in the substitution of tyrosine with histidine in the N-terminal region of transmembrane domain 2 of bestrophin-1. Another novel variant, BEST1 c.867+97G>A (chr11:61725867), located in intron 7, might be considered a regulatory variant that changes allele-specific binding affinity based on motifs of important transcriptional regulators. CONCLUSION: Our findings represent the first use of third-generation sequencing (TGS) to identify novel BEST1 mutations in patients with ARB, indicating that TGS can be a more accurate and efficient tool for identifying mutations in specific genes. The novel variants identified further broaden the mutation spectrum of BEST1 in the Chinese population.

Predicting treatment plan approval probability for high-dose-rate brachytherapy of cervical cancer using adversarial deep learning.

Objective.Predicting the probability of having the plan approved by the physician is important for automatic treatment planning. Driven by the mathematical foundation of deep learning that can use a deep neural network to represent functions accurately and flexibly, we developed a deep-learning framework that learns the probability of plan approval for cervical cancer high-dose-rate brachytherapy (HDRBT).Approach.The system consisted of a dose prediction network (DPN) and a plan-approval probability network (PPN). DPN predicts organs at risk (OAR)D2ccand CTVD90%of the current fraction from the patient's current anatomy and prescription dose of HDRBT. PPN outputs the probability of a given plan being acceptable to the physician based on the patients anatomy and the total dose combining HDRBT and external beam radiotherapy sessions. Training of the networks was achieved by first training them separately for a good initialization, and then jointly via an adversarial process. We collected approved treatment plans of 248 treatment fractions from 63 patients. Among them, 216 plans from 54 patients were employed in a four-fold cross validation study, and the remaining 32 plans from other 9 patients were saved for independent testing.Main results.DPN predicted equivalent dose of 2 Gy for bladder, rectum, sigmoidD2ccand CTVD90%with a relative error of 11.51% ± 6.92%, 8.23% ± 5.75%, 7.12% ± 6.00%, and 10.16% ± 10.42%, respectively. In a task that differentiates clinically approved plans and disapproved plans generated by perturbing doses in ground truth approved plans by 20%, PPN achieved accuracy, sensitivity, specificity, and area under the curve 0.70, 0.74, 0.65, and 0.74.Significance.We demonstrated the feasibility of developing a novel deep-learning framework that predicts a probability of plan approval for HDRBT of cervical cancer, which is an essential component in automatic treatment planning.

Conserved molecular chaperone PrsA stimulates protective immunity against group A Streptococcus.

Group A Streptococcus (GAS) is a significant human pathogen that poses a global health concern. However, the development of a GAS vaccine has been challenging due to the multitude of diverse M-types and the risk of triggering cross-reactive immune responses. Our previous research has identified a critical role of PrsA1 and PrsA2, surface post-translational molecular chaperone proteins, in maintaining GAS proteome homeostasis and virulence traits. In this study, we aimed to further explore the potential of PrsA1 and PrsA2 as vaccine candidates for preventing GAS infection. We found that PrsA1 and PrsA2 are highly conserved among GAS isolates, demonstrating minimal amino acid variation. Antibodies specifically targeting PrsA1/A2 showed no cross-reactivity with human heart proteins and effectively enhanced neutrophil opsonophagocytic killing of various GAS serotypes. Additionally, passive transfer of PrsA1/A2-specific antibodies conferred protective immunity in infected mice. Compared to alum, immunization with CFA-adjuvanted PrsA1/A2 induced higher levels of Th1-associated IgG isotypes and complement activation and provided approximately 70% protection against invasive GAS challenge. These findings highlight the potential of PrsA1 and PrsA2 as universal vaccine candidates for the development of an effective GAS vaccine.

The role of self-related information in the sense of agency.

Sense of agency (SoA) refers to the subjective experience of controlling one's actions and their subsequent consequences. The present study endeavors to investigate the impact of how different degrees of self-related stimuli as action outcomes on the sense of agency by observing the temporal binding effect. Results showed that self-related sound significantly altered temporal binding, notably influencing outcome binding. A post-hoc explanation model effectively elucidated the role of self-related information in the formation of the sense of agency.

Regulation of genes encoding polysaccharide-degrading enzymes in Penicillium.

Penicillium fungi, including Penicillium oxalicum, can secrete a range of efficient plant-polysaccharide-degrading enzymes (PPDEs) that is very useful for sustainable bioproduction, using renewable plant biomass as feedstock. However, the low efficiency and high cost of PPDE production seriously hamper the industrialization of processes based on PPDEs. In Penicillium, the expression of PPDE genes is strictly regulated by a complex regulatory system and molecular breeding to modify this system is a promising way to improve fungal PPDE yields. In this mini-review, we present an update on recent research progress concerning PPDE distribution and function, the regulatory mechanism of PPDE biosynthesis, and molecular breeding to produce PPDE-hyperproducing Penicillium strains. This review will facilitate future development of fungal PPDE production through metabolic engineering and synthetic biology, thereby promoting PPDE industrial biorefinery applications. KEY POINTS: • This mini review summarizes PPDE distribution and function in Penicillium. • It updates progress on the regulatory mechanism of PPDE biosynthesis in Penicillium. • It updates progress on breeding of PPDE-hyperproducing Penicillium strains.

Acupoint application therapy alleviates pain by regulating immune function through inhibiting TLR4/MyD88/NF-κB p65 signaling in a primary dysmenorrhea rat model. / 穴位贴敷通过TLR4/MyD88/NF-κBé€šè·¯è°ƒèŠ‚åŽŸå‘æ€§ç—›ç»å¤§é¼ çš„å ç–«åŠŸèƒ½.

OBJECTIVES: To investigate the effects of graphene-based warm uterus acupoint paste on uterine Toll-like receptor 4 (TLR4)/myeloid differentiation factor 88 (MyD88)/nuclear transcription factor-kappa B p65 (NF-κB p65) signaling pathway and Th1/Th2 immune balance in primary dysmenorrhea ( PD ) model rats, so as to reveal its immunological mechanisms of relieving dysmenorrhea. METHODS: Thirty SD female rats were randomly divided into 3 groups：normal group, model group and acupoint paste group, with 10 rats in each group. PD rat model was established by subcutaneous injection of estradiol benzoate for 10 consecutive days. At the same time of modeling, graphene-based warm uterus acupoint paste was applied to the acupoints of "Guanyuan" (CV4), bilateral "Zigong" (EX-CA1) and "Sanyinjiao" (SP6) of rats in the acupoint paste group. The application was continuously applied once daily for 10 d, 5 h each time. On the 11th day, oxytocin was injected intraperitoneally to observe the writhing latency, writhing times within 30 min and writhing score of rats in each group. The spleen and thymus indexes were calculated. The pathological changes of spleen and thymus tissue were observed after HE staining. The contents of serum immunoglobulin (Ig) A, IgG, tumor necrosis factor-α (TNF-α), interleukin (IL)-2, interferon-γ (IFN-γ), IL-4 and IL-10 were detected by ELISA . The protein and mRNA expression levels of TLR4, MyD88 and NF-κB p65 in rat uterine tissue were detected by Western blot and real-time quantitative PCR, respectively. RESULTS: Compared with the normal group, the writhing times and writhing scores within 30 min of rats in the model group were significantly increased(P<0.001), and the rats showed writhing reaction (P<0.01). The spleen index and thymus index were significantly decreased(P<0.01, P<0.05). The spleen and thymus had obvious pathological changes. The contents of IgA, IgG, TNF-α, IL-2 and IFN-γ in serum were significantly increased, while the contents of serum IL-4 and IL-10 were significantly decreased(P<0.001, P<0.01). The expression levels of TLR4, MyD88, NF-κB p65 protein and corresponding mRNA in uterine tissue were significantly increased(P<0.001). Following intervention, compared with the model group, the writhing latency time of rats in the acupoint paste group was prolonged, and the writhing times and writhing scores within 30 min were significantly decreased (P<0.001). The spleen index and thymus index were significantly increased(P<0.01, P<0.05). The pathological changes of spleen and thymus were improved. The contents of serum IgA, IgG, TNF-α, IL-2 and IFN-γ were significantly decreased, while the contents of IL-4 and IL-10 were significantly increased(P<0.001, P<0.05, P<0.01). The expression of TLR4, MyD88, NF-κB p65 protein and the corresponding mRNA levels in uterine tissue were decreased(P<0.001, P<0.01). CONCLUSIONS: Graphene-based warm uterus acupoint paste can regulate the immune balance of Th1/ Th2 by regulating TLR4/ MyD88/ NF-κB p65 signaling pathway, repair the pathological damage of immune tissue, improve immune function, and effectively relieve the pain symptoms of PD rats.

Design, synthesis and evaluation of antioxidant and anti-inflammatory activities of novel resveratrol derivatives as potential multifunctional drugs.

Oxidative stress and inflammation responses are closely related to the occurrence and development of many diseases. Therefore, anti-oxidation and anti-inflammation have become hot spots in the treatment of diseases. A series of novel resveratrol derivatives which hybrid with benzoylhydrazines were designed, synthesized and assessed for their in vitro antioxidant and anti-inflammatory activity. Initially, the antioxidant abilities of resveratrol derivatives were investigated by DPPH, ABTS radical scavenging and FRAP assays. RAW 264.7 macrophages are routinely used to evaluate the antioxidant and anti-inflammatory activities of drugs, so we used it to construct cell models of oxidative stress and inflammation. Among all the derivatives, compound 5 exhibited superior ROS- and NO-inhibitory activities. The molecular mechanism detected by Western blotting showed that compound 5 could significantly activate the Nrf2 signaling pathway and up-regulate the expression of HO-1 to resist oxidative stress stimulated by H2O2. At the same time, it could down-regulate the expression of apoptosis-related proteins Caspase3 and PARP, alleviating cells damage and apoptosis. In addition, compound 5 dose-dependently inhibited the activation of NF-κB p65/iNOS and MAPKs signaling pathway.

Feasibility of Synchrotron-Based Ultra-High Dose Rate (UHDR) Proton Irradiation with Pencil Beam Scanning for FLASH Research.

BACKGROUND: This study aims to present the feasibility of developing a synchrotron-based proton ultra-high dose rate (UHDR) pencil beam scanning (PBS) system. METHODS: The RF extraction power in the synchrotron system was increased to generate 142.4 MeV pulsed proton beams for UHDR irradiation at ~100 nA beam current. The charge per spill was measured using a Faraday cup. The spill length and microscopic time structure of each spill was measured with a 2D strip transmission ion chamber. The measured UHDR beam fluence was used to derive the spot dwell time for pencil beam scanning. Absolute dose distributions at various depths and spot spacings were measured using Gafchromic films in a solid-water phantom. RESULTS: For proton UHDR beams at 142.4 MeV, the maximum charge per spill is 4.96 ± 0.10 nC with a maximum spill length of 50 ms. This translates to an average beam current of approximately 100 nA during each spill. Using a 2 × 2 spot delivery pattern, the delivered dose per spill at 5 cm and 13.5 cm depth is 36.3 Gy (726.3 Gy/s) and 56.2 Gy (1124.0 Gy/s), respectively. CONCLUSIONS: The synchrotron-based proton therapy system has the capability to deliver pulsed proton UHDR PBS beams. The maximum deliverable dose and field size per pulse are limited by the spill length and extraction charge.

Virtual dosimetry study with three cone-beam breast computed tomography scanners using a fast GPU-based Monte Carlo code.

Objective. To compare the dosimetric performance of three cone-beam breast computed tomography (BCT) scanners, using real-time Monte Carlo-based dose estimates obtained with the virtual clinical trials (VCT)-BREAST graphical processing unit (GPU)-accelerated platform dedicated to VCT in breast imaging. Approach. A GPU-based Monte Carlo (MC) code was developed for replicatingin silicothe geometric, x-ray spectra and detector setups adopted, respectively, in two research scanners and one commercial BCT scanner, adopting 80 kV, 60 kV and 49 kV tube voltage, respectively. Our cohort of virtual breasts included 16 anthropomorphic voxelized breast phantoms from a publicly available dataset. For each virtual patient, we simulated exams on the three scanners, up to a nominal simulated mean glandular dose of 5 mGy (primary photons launched, in the order of 1011-1012per scan). Simulated 3D dose maps (recorded for skin, adipose and glandular tissues) were compared for the same phantom, on the three scanners. MC simulations were implemented on a single NVIDIA GeForce RTX 3090 graphics card.Main results.Using the spread of the dose distribution as a figure of merit, we showed that, in the investigated phantoms, the glandular dose is more uniform within less dense breasts, and it is more uniformly distributed for scans at 80 kV and 60 kV, than at 49 kV. A realistic virtual study of each breast phantom was completed in about 3.0 h with less than 1% statistical uncertainty, with 109primary photons processed in 3.6 s computing time.Significance. We reported the first dosimetric study of the VCT-BREAST platform, a fast MC simulation tool for real-time virtual dosimetry and imaging trials in BCT, investigating the dose delivery performance of three clinical BCT scanners. This tool can be adopted to investigate also the effects on the 3D dose distribution produced by changes in the geometrical and spectrum characteristics of a cone-beam BCT scanner.

Definitive radiation for advanced cervix cancer is not associated with vaginal shortening-a prospective vaginal length and dose correlation.

PURPOSE: Prospectively measure change in vaginal length after definitive chemoradiation (C-EBRT) with Intracavitary Brachytherapy (ICBT) for locally advanced cervix cancer (LACC) and correlate with vaginal dose (VD). MATERIALS AND METHODS: Twenty one female patients with LACC receiving C-EBRT and ICBT underwent serial vaginal length (VL) measurements. An initial measurement was made at the time of the first ICBT procedure and subsequently at 3 month intervals up to 1 year post radiation. The vagina was contoured as a 3-dimensional structure for each brachytherapy plan. The difference in VL before and at least 6 months after the last fraction of brachytherapy was considered as an indicator of toxicity. RESULTS: The mean initial VL was 8.7 cm (6.5-12) with median value of 8.5 cm. The mean VL after 6 months was 8.6 cm (6.5-12) and VL change was not found to be statistically significant. The median values (interquartile ranges) for vaginal D0.1cc, D1cc, and D2cc were 129.2 Gy (99.6-252.2), 96.9 Gy (84.2-114.9), and 89.6 Gy (82.4-102.2), respectively. No significant correlation was found between vaginal length change and the dosimetric parameters calculated for all patients. CONCLUSION: Definitive C-EBRT and ICBT did not significantly impact VL in this prospective cohort probably related to acceptable doses per ICRU constraints. Estimate of vaginal stenosis and sexual function was not performed in this cohort which is a limitation of this study and which we hope to study prospectively going forward.

ART2Dose: A comprehensive dose verification platform for online adaptive radiotherapy.

BACKGROUND: Online adaptive radiotherapy (ART) involves the development of adaptable treatment plans that consider patient anatomical data obtained right prior to treatment administration, facilitated by cone-beam computed tomography guided adaptive radiotherapy (CTgART) and magnetic resonance image-guided adaptive radiotherapy (MRgART). To ensure accuracy of these adaptive plans, it is crucial to conduct calculation-based checks and independent verification of volumetric dose distribution, as measurement-based checks are not practical within online workflows. However, the absence of comprehensive, efficient, and highly integrated commercial software for secondary dose verification can impede the time-sensitive nature of online ART procedures. PURPOSE: The main aim of this study is to introduce an efficient online quality assurance (QA) platform for online ART, and subsequently evaluate it on Ethos and Unity treatment delivery systems in our clinic. METHODS: To enhance efficiency and ensure compliance with safety standards in online ART, ART2Dose, a secondary dose verification software, has been developed and integrated into our online QA workflow. This implementation spans all online ART treatments at our institution. The ART2Dose infrastructure comprises four key components: an SQLite database, a dose calculation server, a report generator, and a web portal. Through this infrastructure, file transfer, dose calculation, report generation, and report approval/archival are seamlessly managed, minimizing the need for user input when exporting RT DICOM files and approving the generated QA report. ART2Dose was compared with Mobius3D in pre-clinical evaluations on secondary dose verification for 40 adaptive plans. Additionally, a retrospective investigation was conducted utilizing 1302 CTgART fractions from ten treatment sites and 1278 MRgART fractions from seven treatment sites to evaluate the practical accuracy and efficiency of ART2Dose in routine clinical use. RESULTS: With dedicated infrastructure and an integrated workflow, ART2Dose achieved gamma passing rates that were comparable to or higher than those of Mobius3D. Additionally, it significantly reduced the time required to complete pre-treatment checks by 3-4 min for each plan. In the retrospective analysis of clinical CTgART and MRgART fractions, ART2Dose demonstrated average gamma passing rates of 99.61 ± 0.83% and 97.75 ± 2.54%, respectively, using the 3%/2 mm criteria for region greater than 10% of prescription dose. The average calculation times for CTgART and MRgART were approximately 1 and 2 min, respectively. CONCLUSION: Overall, the streamlined implementation of ART2Dose notably enhances the online ART workflow, offering reliable and efficient online QA while reducing time pressure in the clinic and minimizing labor-intensive work.

Spectral CT image reconstruction using a constrained optimization approach-An algorithm for AAPM 2022 spectral CT grand challenge and beyond.

BACKGROUND: CT reconstruction is of essential importance in medical imaging. In 2022, the American Association of Physicists in Medicine (AAPM) sponsored a Grand Challenge to investigate the challenging inverse problem of spectral CT reconstruction, with the aim of achieving the most accurate reconstruction results. The authors of this paper participated in the challenge and won as a runner-up team. PURPOSE: This paper reports details of our PROSPECT algorithm (Prior-based Restricted-variable Optimization for SPEctral CT) and follow-up studies regarding the algorithm's accuracy and enhancement of its convergence speed. METHODS: We formulated the reconstruction task as an optimization problem. PROSPECT employed a one-step backward iterative scheme to solve this optimization problem by allowing estimation of and correction for the difference between the actual polychromatic projection model and the monochromatic model used in the optimization problem. PROSPECT incorporated various forms of prior information derived by analyzing training data provided by the Grand Challenge to reduce the number of unknown variables. We investigated the impact of projection data precision on the resulting solution accuracy and improved convergence speed of the PROSPECT algorithm by incorporating a beam-hardening correction (BHC) step in the iterative process. We also studied the algorithm's performance under noisy projection data. RESULTS: Prior knowledge allowed a reduction of the number of unknown variables by 85.9%. PROSPECT algorithm achieved the average root of mean square error (RMSE) of 3.3 × 10 - 6 $3.3\,\times \,10^{-6}$ in the test data set provided by the Grand Challenge. Performing the reconstruction with the same algorithm but using double-precision projection data reduced RMSE to 1.2 × 10 - 11 $1.2\,\times \,10^{-11}$ . Including the BHC step in the PROSPECT algorithm accelerated the iteration process with a 40% reduction in computation time. CONCLUSIONS: PROSPECT algorithm achieved a high degree of accuracy and computational efficiency.

Content specificity of attentional bias to COVID-19 threat-related information in trait anxiety.

Introduction: Anxious individuals selectively attend to threatening information, but it remains unclear whether attentional bias can be generalized to traumatic events, such as the COVID-19 pandemic. Previous studies suggested that specific threats related to personal experiences can elicit stronger attentional bias than general threats. The current study aimed to investigate the relationship between content-specific attentional bias and trait anxiety during the COVID-19 pandemic. Methods: Attentional bias was assessed using the dot-probe task with COVID-19-related, general threat-related, and neutral words at two exposure times, 200 and 500 ms. Results: We found participants with high trait anxiety exhibited attentional bias toward COVID-19- related stimuli and attentional bias away from general threat-related stimuli, while participants with low trait anxiety showed attentional bias away from both types of stimuli. Discussion: Results suggest that individuals with high trait anxiety show a content-specific attentional bias to COVID-19-related information during the COVID-19 pandemic. Apart from the innate attentional bias toward biological threats, individuals with high trait anxiety may also learn from trauma and develop trauma-specific attentional bias.

Every road leads to Rome: diverse biosynthetic regulation of plant cell wall-degrading enzymes in filamentous fungi Penicillium oxalicum and Trichoderma reesei.

Cellulases and xylanases are plant cell wall-degrading enzymes (CWDEs) that are critical to sustainable bioproduction based on renewable lignocellulosic biomass to reduce carbon dioxide emission. Currently, these enzymes are mainly produced from filamentous fungi, especially Trichoderma reesei and Penicillium oxalicum. However, an in-depth comparison of these two producers has not been performed. Although both P. oxalicum and T. reesei harbor CWDE systems, they exhibit distinct features regulating the production of these enzymes, mainly through different transcriptional regulatory networks. This review presents the strikingly different modes of genome-wide regulation of cellulase and xylanase biosynthesis in P. oxalicum and T. reesei, including sugar transporters, signal transduction cascades, transcription factors, chromatin remodeling, and three-dimensional organization of chromosomes. In addition, different molecular breeding approaches employed, based on the understanding of the regulatory networks, are summarized. This review highlights the existence of very different regulatory modes leading to the efficient regulation of CWDE production in filamentous fungi, akin to the adage that "every road leads to Rome." An understanding of this divergence may help further improvements in fungal enzyme production through the metabolic engineering and synthetic biology of certain fungal species.

Improvement of triterpenoid production in mycelia of Antrodia camphorata through mutagenesis breeding and amelioration of CCl4-induced liver injury in mice.

Due to the scarcity of wild fruiting bodies, submerged fermentation of the medicinal fungus Antrodia camphorata is attracting much attention, but the production of bioactive triterpenoids is low. Therefore, there is an urgent need to improve the triterpenoid yield of submerged fermentation. Here, the A. camphorata mutant E3-64 was generated from strain AC16101 through random mutagenesis breeding, producing 172.8 mg triterpenoid per gram of dry mycelia. Further optimization of culture parameters resulted in a yield of 255.5 mg/g dry mycelia (i.e., an additional >1.4-fold increase), which is the highest reported yield thus far. Notably, mutant E3-64 produced 94% and 178% more of the triterpenoid components antcin A and antcamphin A, respectively, while it produced 52% and 15% less antcin B and G, respectively. Mutant E3-64 showed increased expression of key genes involved in triterpenoid biosynthesis, as well as different genome-wide single-nucleotide polymorphisms as compared with AC16101. Triterpenoids of the E3-64 mycelia exhibited remarkably protective activity against acute CCl4-induced liver injury in mice. This study shows the potential of A. camphorata for scientific research and commercial application.

Regulation of fungal raw-starch-degrading enzyme production depends on transcription factor phosphorylation and recruitment of the Mediator complex.

Filamentous fungus can produce raw-starch-degrading enzyme (RSDE) that efficiently degrades raw starch below starch gelatinization temperature. Employment of RSDE in starch processing can save energy. A key putative transcription factor PoxRsrA (production of raw-starch-degrading enzyme regulation in Penicillium oxalicum) was identified to regulate RSDE production in P. oxalicum; however, its regulatory mechanism remains unclear. Here we show that PoxRsrA1434-1730 was the transcriptional activation domain, with essential residues, D1508, W1509 and M1510. SANT (SWI3, ADA2, N-CoR and TFIIIB)-like domain 1 (SANT1) bound to DNA at the sequence 5'-RHCDDGGD-3' in the promoter regions of genes encoding major amylases, with an essential residue, R866. SANT2 interacted with a putative 3-hydroxyisobutyryl-CoA hydrolase, which suppressed phosphorylation at tyrosines Y1127 and Y1170 of PoxRsrA901-1360, thereby inhibiting RSDE biosynthesis. PoxRsrA1135-1439 regulated mycelial sporulation by interacting with Mediator subunit Med6, whereas PoxRsrA1440-1794 regulated RSDE biosynthesis by binding to Med31. Overexpression of PoxRsrA increased sporulation and RSDE production. These findings provide insights into the regulatory mechanisms of fungal RSDE biosynthesis.