HiOmics: A cloud-based one-stop platform for the comprehensive analysis of large-scale omics data

Analyzing the vast amount of omics data generated comprehensively by high-throughput sequencing technology is of utmost importance for scientists. In this context, we propose HiOmics, a cloud-based platform equipped with nearly 300 plugins designed for the comprehensive analysis and visualization of omics data. HiOmics utilizes the Element Plus framework to craft a user-friendly interface and harnesses Docker container technology to ensure the reliability and reproducibility of data analysis results. Furthermore, HiOmics employs the Workflow Description Language and Cromwell engine to construct workflows, ensuring the portability of data analysis and simplifying the examination of intricate data. Additionally, HiOmics has developed DataCheck, a tool based on Golang, which verifies and converts data formats. Finally, by leveraging the object storage technology and batch computing capabilities of public cloud platforms, HiOmics enables the storage and processing of large-scale data while maintaining resource independence among users.

EndoSRR: a comprehensive multi-stage approach for endoscopic specular reflection removal

PURPOSE

Specular reflections in endoscopic images not only disturb visual perception but also hamper computer vision algorithm performance. However, the intricate nature and variability of these reflections, coupled with a lack of relevant datasets, pose ongoing challenges for removal.

METHODS

We present EndoSRR, a robust method for eliminating specular reflections in endoscopic images. EndoSRR comprises two stages: reflection detection and reflection region inpainting. In the reflection detection stage, we adapt and fine-tune the segment anything model (SAM) using a weakly labeled dataset, achieving an accurate reflection mask. For reflective region inpainting, we employ LaMa, a fast Fourier convolution-based model trained on a 4.5M-image dataset, enabling effective inpainting of arbitrarily shaped reflection regions. Lastly, we introduce an iterative optimization strategy for dual pre-trained models to refine the results of specular reflection removal, named DPMIO.

RESULTS

Utilizing the SCARED-2019 dataset, our approach surpasses state-of-the-art methods in both qualitative and quantitative evaluations. Qualitatively, our method excels in accurately detecting reflective regions, yielding more natural and realistic inpainting results. Quantitatively, our method demonstrates superior performance in both segmentation evaluation metrics (IoU, E-measure, etc.) and image inpainting evaluation metrics (PSNR, SSIM, etc.).

CONCLUSION

The experimental results underscore the significance of proficient endoscopic specular reflection removal for enhancing visual perception and downstream tasks. The methodology and results presented in this study are poised to catalyze advancements in specular reflection removal, thereby augmenting the accuracy and safety of minimally invasive surgery.

Self-Assembling Sulfated Lactobacillus Exopolysaccharide Nanoparticles as Adjuvants for SARS-CoV-2 Subunit Vaccine Elicit Potent Humoral and Cellular Immune Responses

Coronavirus disease 2019 (COVID-19) has caused a global pandemic since its onset in 2019, and the development of effective vaccines for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to induce potent and long-lasting immunity remains a priority. Herein, we prepared two Lactobacillus exopolysaccharide (EPS) nanoparticle adjuvants (NPs 7-4 and NPs 8-2) that were constructed by using sulfation-modified EPS and quaternization-modified chitosan. These two NPs displayed a spherical morphology with sizes of 39 and 47 nm. Furthermore, the zeta potentials of NPs 7-4 and NPs 8-2 were 50.40 and 44.40 mV, respectively. In vitro assays demonstrated that NPs could effectively adsorb antigenic proteins and exhibited a sustained release effect. Mouse immunization tests showed that the NPs induced the expression of cytokines and chemokines at the injection site and promoted the uptake of antigenic proteins by macrophages. Mechanically, the NPs upregulated the expression of pattern recognition receptors (toll-like receptors and nod-like receptors) and activated the immune response of T cells and the production of neutralizing antibodies. In addition, the NP adjuvants had favorable immune-enhancing effects in cats, which are of great significance for controlling the trans-host transmission and re-endemicity of SARS-CoV-2. Overall, we demonstrated that NP-adjuvanted SARS-CoV-2 receptor binding domain proteins could induce robust specific humoral and cellular immunity.

Active Dendrite Suppression by Ferroelectric Membrane Separators in Rechargeable Batteries

Anodic dendrite formation is a critical issue in rechargeable batteries and often leads to poor cycling stability and quick capacity loss. Prevailing strategies for dendrite suppression aim at slowing down the growth rate kinetically but still leaving possibilities for dendrite evolution over time. Herein, we report a complete dendrite elimination strategy using a mesoporous ferroelectric polymer membrane as the battery separator. The dendrite suppression is realized by spontaneously reversing the surface energetics for metal ion reduction at the protrusion front, where a positive piezoelectric polarization is generated and superimposed as the protrusion compresses the separator. This effect is demonstrated first in a Zn electroplating process, and further in Zn-Zn symmetric cells and Zn-NaV3O8·1.5H2O full cells, where the dendritic Zn anode surfaces are completely turned into featureless flat surfaces. Consequently, a substantially longer charging/discharging cycle is achieved. This study provides a promising pathway toward high-performance dendrite-free rechargeable batteries.

Rapid and accurate quality evaluation of Angelicae Sinensis Radix based on near-infrared spectroscopy and Bayesian optimized LSTM network

The authentic traditional Chinese medicines (TCMs) including Angelicae Sinensis Radix (ASR) are the representative of high-quality herbals in China. However, ASR from authentic region being adulterated or counterfeited is frequently occurring, and there is still a lack of rapid quality evaluation methods for identifying the authentic ASR. In this study, the color features of ASR were firstly characterized. The results showed that the authentic ASR cannot be fully identified by color characteristics. Then near-infrared (NIR) spectroscopy combined with Bayesian optimized long short-term memory (BO-LSTM) was used to evaluate the quality of ASR, and the performance of BO-LSTM with common classification and regression algorithms was compared. The results revealed that following the pretreatment of NIR spectra, the optimal NIR spectra combined with BO-LSTM not only successfully distinguished authentic, non-authentic, and adulterated ASR with 100 % accuracy, but also accurately predicted the adulteration concentration of authentic ASR (R2 > 0.99). Moreover, BO-LSTM demonstrated excellent performance in classification and regression compared with common algorithms (ANN, SVM, PLSR, etc.). Overall, the proposed strategy could quickly and accurately evaluate the quality of ASR, which provided a reference for other TCMs.

Dynamics of magnetization at infinite temperature in a Heisenberg spin chain

Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain's center, [Formula: see text]. The first two moments of [Formula: see text] show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.

Deteriorated bone microarchitecture caused by sympathetic overstimulation in pheochromocytoma and paraganglioma

PURPOSE

Despite the potentially destructive effect of sympathetic activity on bone metabolism, its impact on bone microarchitecture, a key determinant of bone quality, has not been thoroughly investigated. This study aims to evaluate the impact of sympathetic activity on bone microarchitecture and bone strength in patients with pheochromocytoma and paraganglioma (PPGL).

METHODS

A cross-sectional study was conducted in 38 PPGL patients (15 males and 23 females). Bone turnover markers serum procollagen type 1 N-terminal propeptide (P1NP) and β-carboxy-terminal crosslinked telopeptide of type 1 collagen (β-CTX) were measured. 24-h urinary adrenaline (24hUE) and 24-h urinary norepinephrine levels (24hUNE) were measured to indicate sympathetic activity. High-resolution peripheral quantitative computed tomography (HR-pQCT) was conducted to evaluate bone microarchitecture in PPGL patients and 76 age-, sex-matched healthy controls (30 males and 46 females). Areal bone mineral density (aBMD) was measured by dual-energy X-ray absorptiometry (DXA) simultaneously.

RESULTS

PPGL patients had a higher level of β-CTX. HR-pQCT assessment revealed that PPGL patients had notably thinner and more sparse trabecular bone (decreased trabecular number and thickness with increased trabecular separation), significantly decreased volume BMD (vBMD), and bone strength at both the radius and tibia compared with healthy controls. The deterioration of Tt.vBMD, Tb.Sp, and Tb.1/N.SD was more pronounced in postmenopausal patients compared with the premenopausal subjects. Moreover, subjects in the highest 24hUNE quartile (Q4) showed markedly lower Tb.N and higher Tb.Sp and Tb.1/N.SD at the tibia than those in the lowest quartile (Q1). Age-related bone loss was also exacerbated in PPGL patients to a certain extent.

CONCLUSIONS

PPGL patients had significantly deteriorated bone microarchitecture and strength, especially in the trabecular bone, with an increased bone resorption rate. Our findings provide clinical evidence that sympathetic overstimulation may serve as a secondary cause of osteoporosis, especially in subjects with increased sympathetic activity.

Application of deep learning in radiation therapy for cancer

In recent years, with the development of artificial intelligence, deep learning has been gradually applied to clinical treatment and research. It has also found its way into the applications in radiotherapy, a crucial method for cancer treatment. This study summarizes the commonly used and latest deep learning algorithms (including transformer, and diffusion models), introduces the workflow of different radiotherapy, and illustrates the application of different algorithms in different radiotherapy modules, as well as the defects and challenges of deep learning in the field of radiotherapy, so as to provide some help for the development of automatic radiotherapy for cancer.

[Clinical application of split liver transplantation: a single center report of 203 cases]

Objective: To investigate the safety and therapeutic effect of split liver transplantation (SLT) in clinical application. Methods: This is a retrospective case-series study. The clinical data of 203 consecutive SLT, 79 living donor liver transplantation (LDLT) and 1 298 whole liver transplantation (WLT) performed at the Third Affiliated Hospital of Sun Yat-sen University from July 2014 to July 2023 were retrospectively analyzed. Two hundred and three SLT liver grafts were obtained from 109 donors. One hundred and twenty-seven grafts were generated by in vitro splitting and 76 grafts were generated by in vivo splitting. There were 90 adult recipients and 113 pediatric recipients. According to time, SLT patients were divided into two groups: the early SLT group (40 cases, from July 2014 to December 2017) and the mature SLT technology group (163 cases, from January 2018 to July 2023). The survival of each group was analyzed and the main factors affecting the survival rate of SLT were analyzed. The Kaplan-Meier method and Log-rank test were used for survival analysis. Results: The cumulative survival rates at 1-, 3-, and 5-year were 74.58%, 71.47%, and 71.47% in the early SLT group, and 88.03%, 87.23%, and 87.23% in the mature SLT group, respectively. Survival rates in the mature SLT group were significantly higher than those in the early SLT group (χ2=5.560,P=0.018). The cumulative survival rates at 1-, 3- and 5-year were 93.41%, 93.41%, 89.95% in the LDLT group and 87.38%, 81.98%, 77.04% in the WLT group, respectively. There was no significant difference among the mature SLT group, the LDLT group and the WLT group (χ2=4.016, P=0.134). Abdominal hemorrhage, infection, primary liver graft nonfunction,and portal vein thrombosis were the main causes of early postoperative death. Conclusion: SLT can achieve results comparable to those of WLT and LDLT in mature technology liver transplant centers, but it needs to go through a certain time learning curve.

Measurements of All-Particle Energy Spectrum and Mean Logarithmic Mass of Cosmic Rays from 0.3 to 30 PeV with LHAASO-KM2A

We present the measurements of all-particle energy spectrum and mean logarithmic mass of cosmic rays in the energy range of 0.3-30 PeV using data collected from LHAASO-KM2A between September 2021 and December 2022, which is based on a nearly composition-independent energy reconstruction method, achieving unprecedented accuracy. Our analysis reveals the position of the knee at 3.67±0.05±0.15  PeV. Below the knee, the spectral index is found to be -2.7413±0.0004±0.0050, while above the knee, it is -3.128±0.005±0.027, with the sharpness of the transition measured with a statistical error of 2%. The mean logarithmic mass of cosmic rays is almost heavier than helium in the whole measured energy range. It decreases from 1.7 at 0.3 PeV to 1.3 at 3 PeV, representing a 24% decline following a power law with an index of -0.1200±0.0003±0.0341. This is equivalent to an increase in abundance of light components. Above the knee, the mean logarithmic mass exhibits a power law trend towards heavier components, which is reversal to the behavior observed in the all-particle energy spectrum. Additionally, the knee position and the change in power-law index are approximately the same. These findings suggest that the knee observed in the all-particle spectrum corresponds to the knee of the light component, rather than the medium-heavy components.

Recurrent neural network-based simultaneous cardiac T1, T2, and T1ρ mapping

The purpose of the current study was to explore the feasibility of training a deep neural network to accelerate the process of generating T1, T2, and T1ρ maps for a recently proposed free-breathing cardiac multiparametric mapping technique, where a recurrent neural network (RNN) was utilized to exploit the temporal correlation among the multicontrast images. The RNN-based model was developed for rapid and accurate T1, T2, and T1ρ estimation. Bloch simulation was performed to simulate a dataset of more than 10 million signals and time correspondences with different noise levels for network training. The proposed RNN-based method was compared with a dictionary-matching method and a conventional mapping method to evaluate the model's effectiveness in phantom and in vivo studies at 3 T, respectively. In phantom studies, the RNN-based method and the dictionary-matching method achieved similar accuracy and precision in T1, T2, and T1ρ estimations. In in vivo studies, the estimated T1, T2, and T1ρ values obtained by the two methods achieved similar accuracy and precision for 10 healthy volunteers (T1: 1228.70 ± 53.80 vs. 1228.34 ± 52.91 ms, p > 0.1; T2: 40.70 ± 2.89 vs. 41.19 ± 2.91 ms, p > 0.1; T1ρ: 45.09 ± 4.47 vs. 45.23 ± 4.65 ms, p > 0.1). The RNN-based method can generate cardiac multiparameter quantitative maps simultaneously in just 2 s, achieving 60-fold acceleration compared with the dictionary-matching method. The RNN-accelerated method offers an almost instantaneous approach for reconstructing accurate T1, T2, and T1ρ maps, being much more efficient than the dictionary-matching method for the free-breathing multiparametric cardiac mapping technique, which may pave the way for inline mapping in clinical applications.

Stable quantum-correlated many-body states through engineered dissipation

Engineered dissipative reservoirs have the potential to steer many-body quantum systems toward correlated steady states useful for quantum simulation of high-temperature superconductivity or quantum magnetism. Using up to 49 superconducting qubits, we prepared low-energy states of the transverse-field Ising model through coupling to dissipative auxiliary qubits. In one dimension, we observed long-range quantum correlations and a ground-state fidelity of 0.86 for 18 qubits at the critical point. In two dimensions, we found mutual information that extends beyond nearest neighbors. Lastly, by coupling the system to auxiliaries emulating reservoirs with different chemical potentials, we explored transport in the quantum Heisenberg model. Our results establish engineered dissipation as a scalable alternative to unitary evolution for preparing entangled many-body states on noisy quantum processors.

Strictureplasty may lead to increased preference in the surgical management of Crohn's disease: a case-matched study

BACKGROUND

Resection and strictureplasty are the two surgical modalities used in the management of Crohn's disease (CD). The objective of this study was to compare morbidity and clinical recurrence between patients who underwent strictureplasty and patients who underwent resection.

METHODS

Patients with CD who underwent strictureplasty between January 2012 and December 2022 were enrolled. The patients were well matched with patients who underwent resection without strictureplasty. Patient- and disease-specific characteristics, postoperative morbidity, and clinical recurrence were also analyzed.

RESULTS

A total of 118 patients who underwent a total of 192 strictureplasties were well matched to 118 patients who underwent resection. The strictureplasty group exhibited significantly less blood loss (30 ml versus 50 ml, p < 0.001) and stoma creation (2.5% versus 16.9%, p < 0.001). No significant difference was found regarding postoperative complications or length of postoperative stay. At the end of the follow-up, the overall rate of clinical recurrence was 39.4%, and no difference was observed between the two groups. Postoperative prophylactic use of biologics (odds ratio = 0.2, p < 0.001) was the only protective factor against recurrence.

CONCLUSION

Strictureplasty does not increase the risk of complications or recurrence compared with resection. It represents a viable alternative to resection in selected patients, and as such, it should have a broader scope of indications and greater acceptance among surgeons.

Unified construction of relativistic Hamiltonians

It is shown that the four-component (4C), quasi-four-component (Q4C), and exact two-component (X2C) relativistic Hartree-Fock equations can be implemented in a unified manner by making use of the atomic nature of the small components of molecular 4-spinors. A model density matrix approximation can first be invoked for the small-component charge/current density functions, which gives rise to a static, pre-molecular mean field to be combined with the one-electron term. As a result, only the nonrelativistic-like two-electron term of the 4C/Q4C/X2C Fock matrix needs to be updated during the iterations. A "one-center small-component" approximation can then be invoked in the evaluation of relativistic integrals, that is, all atom-centered small-component basis functions are regarded as extremely localized near the position of the atom to which they belong such that they have vanishing overlaps with all small- or large-component functions centered at other nuclei. Under these approximations, the 4C, Q4C, and X2C mean-field and many-electron Hamiltonians share precisely the same structure and accuracy. Beyond these is the effective quantum electrodynamics Hamiltonian that can be constructed in the same way. Such approximations lead to errors that are orders of magnitude smaller than other sources of errors (e.g., truncation errors in the one- and many-particle bases as well as uncertainties of experimental measurements) and are, hence, safe to use for whatever purposes. The quaternion forms of the 4C, Q4C, and X2C equations are also presented in the most general way, based on which the corresponding Kramers-restricted open-shell variants are formulated for "high-spin" open-shell systems.

Elevated risk of multimorbidity post-COVID-19 infection: protective effect of vaccination

BACKGROUND

It is unclear how the coronavirus disease 2019 (Covid-19) pandemic has affected multimorbidity incidence among those with one pre-existing chronic condition, as well as how vaccination could modify this association.

AIM

To examine the association of Covid-19 infection with multimorbidity incidence among people with one pre-existing chronic condition, including those with prior vaccination.

DESIGN

Nested case-control study.

METHODS

We conducted a territory-wide nested case-control study with incidence density sampling using Hong Kong electronic health records from public healthcare facilities and mandatory Covid-19 reports. People with one listed chronic condition (based on a list of 30) who developed multimorbidity during 1 January 2020-15 November 2022 were selected as case participants and randomly matched with up to 10 people of the same age, sex and with the same first chronic condition without having developed multimorbidity at that point. Conditional logistic regression was used to estimate adjusted odds ratios (aORs) of multimorbidity.

RESULTS

In total, 127 744 case participants were matched with 1 230 636 control participants. Adjusted analysis showed that there were 28%-increased odds of multimorbidity following Covid-19 [confidence interval (CI) 22% to 36%] but only 3% (non-significant) with prior full vaccination with BNT162b2 or CoronaVac (95% CI -2% to 7%). Similar associations were observed in men, women, older people aged 65 or more, and people aged 64 or younger.

CONCLUSIONS

We found a significantly elevated risk of multimorbidity following a Covid-19 episode among people with one pre-existing chronic condition. Full vaccination significantly reduced this risk increase.

Some Recent Advances in Density-Based Reactivity Theory

Establishing a chemical reactivity theory in density functional theory (DFT) language has been our intense research interest in the past two decades, exemplified by the determination of steric effect and stereoselectivity, evaluation of electrophilicity and nucleophilicity, identification of strong and weak interactions, and formulation of cooperativity, frustration, and principle of chirality hierarchy. In this Featured Article, we first overview the four density-based frameworks in DFT to appreciate chemical understanding, including conceptual DFT, use of density associated quantities, information-theoretic approach, and orbital-free DFT, and then present a few recent advances of these frameworks as well as new applications from our studies. To that end, we will introduce the relationship among these frameworks, determining the entire spectrum of interactions with Pauli energy derivatives, performing topological analyses with information-theoretic quantities, and extending the density-based frameworks to excited states. Applications to examine physiochemical properties in external electric fields and to evaluate polarizability for proteins and crystals are discussed. A few possible directions for future development are followed, with the special emphasis on its merger with machine learning.

Effects of Continuous Nutritional Intervention on Nutritional Status and Serum Albumin During Maintenance Therapy in Children with Acute Lymphoblastic Leukemia

Background

Nutritional imbalances can significantly impact clinical efficacy and chemotherapy tolerance in cases of acute lymphoblastic leukemia. Despite the potential significance, there is limited research in this domain, and clinicians have paid limited attention to it.

Objective

This study aims to investigate the impact of continuous nutritional intervention on pediatric patients with acute lymphoblastic leukemia.

Methods

A comparative analysis was conducted by dividing the children into observation and control groups, examining the effects of intermittent diet intervention and continuous nutrition intervention post-nutritional risk assessment.

Results

After the intervention, the observation group exhibited a higher proportion of good nutrition and elevated serum albumin levels compared to the control group (χ2=4.79, 5.49, P = .029, 0.019, t =-2.819, -5.559, P = .01, P < .001). Additionally, the complication rate in the observation group was significantly lower than that in the control group (χ2=5.247, P = .022).

Conclusions

Continuous nutrition intervention emerges as a valuable strategy for improving the nutritional status and serum albumin levels in children undergoing maintenance treatment for acute lymphoblastic leukemia. Moreover, it contributes to a noteworthy reduction in the incidence of complications.

Effect of occlusal stabilisation splint with or without arthroscopic disc repositioning on condylar bone remodelling in adolescent patients

The aim of this study was to investigate the treatment effects of a stabilisation splint (SS) with and without arthroscopic disc repositioning (ADR) on condylar bone remodelling in adolescent patients with anterior disc displacement without reduction (ADDwoR). Cone beam computed tomography and magnetic resonance imaging were used to analyse condylar bone remodelling, condyle position, and disc position. Twenty-two temporomandibular joints of 14 patients who underwent ADR (age range 12-20 years; mean follow-up 12.5 ± 7.8 months) and 21 temporomandibular joints of 14 patients who did not undergo ADR (age range 13-20 years; mean follow-up 11.1 ± 5.1 months) were included. The change in bone volume (P < 0.001), rate of bone volume change (P < 0.001), and change in condyle height (P = 0.031) were significantly greater in patients with ADR than in those without ADR. The changes in posterior joint space (P = 0.013), superior joint space (P = 0.020), and ratio of condyle sagittal position (P = 0.013) were significantly greater in patients with ADR than in those without ADR. All discs in patients who underwent ADR and one disc in those who did not undergo ADR were backward repositioned. In conclusion, in adolescent patients with ADDwoR, ADR with SS therapy achieved better condyle and disc position than SS therapy alone, and also induced bone generation.

Application of natural language processing to post-structuring of rectal cancer MRI reports

AIM

To evaluate a natural language processing (NLP) system for extracting structured information from the free-form text of rectal cancer magnetic resonance imaging (MRI) reports written in Chinese.

MATERIALS AND METHODS

A rule-based NLP model that could extract 11 key image features of rectal cancer was constructed using 358 MRI reports of rectal cancer written between 2015 and 2021. Fifty reports written before 2015 and 50 written after 2021 were used as test datasets, and the reference standard was determined by manual extraction of information by two radiologists. The length and reporting rate of image features in pre-2015 and post-2021 datasets, as well as the accuracy, precision, recall, and F1 score of feature extraction by the NLP system, were compared. The time required for the NLP to extract data was compared with that required by the radiologists.

RESULTS

Reports written after 2021 had longer diagnostic impression sections than reports written before 2015. The reporting rate of key imaging features of rectal cancer was 36.55% before 2015 and 79.82% after 2021. The accuracy, precision, recall, and F1 score of NLP for correct extraction of values from reports were 93.82%, 95.63%, 87.06%, and 91.15%, respectively, for pre-2015 reports, and 92.55%, 98.53%, 94.15%, and 96.29%, respectively, for post-2021 reports. NLP generated all the structured information in <1 second.

CONCLUSIONS

The NLP system with rule-based pattern matching achieved rapid and accurate structured processing of rectal cancer MRI reports. MRI reports with structured templates are more suitable for NLP-based extraction of information.

Toward the Rational Design of Organic Catalysts for Organocatalysed Atom Transfer Radical Polymerisation

Thanks to their diversity, organic photocatalysts (PCs) have been widely used in manufacturing polymeric products with well-defined molecular weights, block sequences, and architectures. Still, however, more universal property-performance relationships are needed to enable the rational design of such PCs. That is, a set of unique descriptors ought to be identified to represent key properties of the PCs relevant for polymerisation. Previously, the redox potentials of excited PCs (PC*) were used as a good descriptor for characterising very structurally similar PCs. However, it fails to elucidate PCs with diverse chromophore cores and ligands, among which those used for polymerisation are a good representative. As showcased by model systems of organocatalysed atom transfer radical polymerisation (O-ATRP), new universal descriptors accounting for additional factors, such as the binding and density overlap between the PC* and initiator, are proposed and proved to be successful in elucidating the experimental performances of PCs in polymerisation. While O-ATRP is exemplified here, the approach adopted is general for studying other photocatalytic systems.

Tumor resistance to anti-mesothelin CAR-T cells caused by binding to shed mesothelin is overcome by targeting a juxtamembrane epitope

Despite many clinical trials, CAR-T cells are not yet approved for human solid tumor therapy. One popular target is mesothelin (MSLN) which is highly expressed on the surface of about 30% of cancers including mesothelioma and cancers of the ovary, pancreas, and lung. MSLN is shed by proteases that cleave near the C terminus, leaving a short peptide attached to the cell. Most anti-MSLN antibodies bind to shed MSLN, which can prevent their binding to target cells. To overcome this limitation, we developed an antibody (15B6) that binds next to the membrane at the protease-sensitive region, does not bind to shed MSLN, and makes CAR-T cells that have much higher anti-tumor activity than a CAR-T that binds to shed MSLN. We have now humanized the Fv (h15B6), so the CAR-T can be used to treat patients and show that h15B6 CAR-T produces complete regressions in a hard-to-treat pancreatic cancer patient derived xenograft model, whereas CAR-T targeting a shed epitope (SS1) have no anti-tumor activity. In these pancreatic cancers, the h15B6 CAR-T replicates and replaces the cancer cells, whereas there are no CAR-T cells in the tumors receiving SS1 CAR-T. To determine the mechanism accounting for high activity, we used an OVCAR-8 intraperitoneal model to show that poorly active SS1-CAR-T cells are bound to shed MSLN, whereas highly active h15B6 CAR-T do not contain bound MSLN enabling them to bind to and kill cancer cells.

Spectral and conformational characteristics of phycocyanin associated with changes of medium pH

C-phycocyanin (C-PC) is the main component of water-soluble light-harvesting complexes (phycobilisomes, PBS) of cyanobacteria. PBS are involved in the absorption of quantum energy and the transfer of electronic excitation energy to the photosystems. A specific environment of C-PC chromophoric groups is provided by the protein matrix structure including protein-protein contacts between different subunits. Registration of C-PC spectral characteristics and the fluorescence anisotropy decay have revealed a significant pH influence on the chromophore microenvironment: at pH 5.0, a chromophore is more significantly interacts with the solvent, whereas at pH 9.0 the chromophore microenvironment becomes more viscous. Conformations of chromophores and the C-PC protein matrix have been studied by Raman and infrared spectroscopy. A decrease in the medium pH results in changes in the secondary structure either the C-PC apoproteins and chromophores, the last one adopts a more folded conformation.

Involvement of GA3-oxidase in inhibitory effect of nitric oxide on primary root growth in Arabidopsis

Both NO and GAs are essential for regulating various physiological processes and stress responses in plants. However, the interaction between these two molecules remains unclear. We investigated the distinct response patterns of Arabidopsis thaliana Col-0 and GA synthesis functional deficiency mutants to NO by measuring root length. To investigate underlying mechanisms, we detected bioactive GA content using UHPLC-ESI-MS/MS, assessed the accumulation of ROS by chemical staining Arabidopsis roots. We also conducted RNA-seq analysis and compared results between Col-0 and ga3ox1, with and without SNP (as NO donor) treatment. Phenotypic results revealed that the inhibitory effect of NO on primary roots of Arabidopsis was primarily mediated by GA3-oxidase, rather than GA20-oxidase or GA2-oxidase. The content of GA3 decreased in Col-0 treated with SNP, whereas this decrease was not observed in ga3ox1. The deficiency of GA3-oxidase alleviated the buildup of H2 O2 in roots when treated with SNP. We identified 222 DEGs. GO annotation of these DEGs revealed that all top 20 GO terms were related to stress responses. Moreover, three DEGs were annotated to GA-related processes (DDF1, DDF2, EXPA1), and seven DEGs were associated with root development (RAV1, RGF2, ERF71, ZAT6, MYB77, XT1, and DTX50). In summary, NO inhibits primary root growth partially by repressing GA3-oxidase catalysed GA3 synthesis in Arabidopsis. ROS, Ca2+ , DDF1, DDF2, EXPA1 and seven root development-related genes may be involved in crosstalk between NO and GAs.

Causal link between gut microbiota and osteoporosis analyzed via Mendelian randomization

OBJECTIVE

Osteoporosis (OP) is closely associated with gut microbiota (GM), yet the nature of their causal relationship remains elusive. Therefore, this study aims to reverse causality between GM and OP by using population cohorts and two-sample MR (TSMR) analysis.

MATERIALS AND METHODS

In this study, we conducted an extensive genome-wide association study (GWAS) using publicly accessible summary statistics data for GM and OP. Employing rigorous criteria (p < 1*e-5), we identified independent genetic loci that exhibited significant associations with GM relative abundances as instrumental variables (IVs). A causal evaluation was primarily carried out using the inverse variance-weighted (IVW) method, supplemented by additional analyses such as MR-Egger, weighted median, simple mode, and weighted mode.

RESULTS

We unveiled that increased abundances of the family Pasteurellaceae, order Pasteurellales, and genus Ruminococcaceae UCG004 were linked to an increased risk of OP. Conversely, the family Oxalobacteraceae, unknown family id.1000006161, genus Lachnospiraceae NK4A136 group, unknown genus id.1000006162, and order NB1n were associated with a reduced risk of OP. To ensure the reliability of our findings, we conducted quality assessments through Cochrane's Q test and a leave-one-out analysis. Furthermore, the stability and consistency of the results were confirmed by the MR-Egger intercept test, Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) global test, and sensitivity analysis (p > 0.05). Our study reveals the causal relationships between 211 GM taxa and OP, pinpointing specific GM taxa associated with the risk of OP. This research sheds light on the genetic mechanisms that underlie GM-mediated OP and opens up promising avenues for identifying valuable biomarkers and potential therapeutic targets in future OP research.

CONCLUSIONS

This study establishes a substantial GM-OP link with specific taxa being identified, offering biomarkers for early detection, tailored interventions, and improved patient education. These findings enhance OP diagnosis, prevention, and treatment, promising more effective, individualized care and inspiring future research.

Tumor-derived Exosomal ENO2 Modulates Polarization of Tumor-associated Macrophages through Reprogramming Glycolysis to Promote Progression of Diffuse Large B-cell Lymphoma

Macrophages can be polarized into functional classically activated (M1) or alternatively activated (M2) phenotype. Tumor-associated macrophages (TAMs) mainly exhibit M2 phenotype. Previous works determined that up-regulation of enolase 2 (ENO2) in diffuse large B-cell lymphoma (DLBCL) cells can promote macrophages to an M2-like phenotype, thereby consequently promoting the progression of DLBCL. Exosomes are a subset of extracellular vesicles, carrying various bioactive molecules, mediate signals transduction and regulate immune cells. In our study, we investigated the role and related mechanisms of DLBCL-derived exosomal ENO2 in regulating macrophage polarization during DLBCL progression via bioinformatics analysis and a series of experiments. The results of bioinformatics analysis indicated that high expression of ENO2 was positively correlated with DLBCL progression and macrophages M2/M1 ratio. ENO2 protein levels were increased in the exosomes of the sera of DLBCL patients and DLBCL cells. Moreover, the DLBCL-derived exosomes were assimilated by macrophages and then regulated macrophage polarization. The results of in vitro and in vivo experiments showed that DLBCL-derived exosomal ENO2 modulated macrophages polarization (increased M2 phenotype and decreased M1 phenotype), thereby promoting DLBCL proliferation, migration, and invasion. We then revealed that the modulation of macrophages polarization by DLBCL-derived exosomal ENO2 depended on glycolysis and was promoted through GSK3β/β-catenin/c-Myc signaling pathway. These findings suggested that DLBCL-derived exosomal ENO2 accelerated glycolysis via GSK3β/β-catenin/c-Myc signaling pathway to ultimately promote macrophages to an M2-like phenotype, which can promote the proliferation, migration and invasion of DLBCL, suggesting that exosomal ENO2 may be a promising therapeutic target and prognostic biomarker for DLBCL.

Efficacy and Safety of First-line Therapies for Advanced Unresectable Oesophageal Squamous Cell Cancer: a Systematic Review and Network Meta-analysis

AIM

To compare the clinical efficacy and safety of first-line treatments for advanced unresectable oesophageal squamous cell cancer.

MATERIALS AND METHODS

A systematic review and network meta-analysis was carried out by retrieving and retaining relevant literature from databases. The studies were randomised controlled trials comparing first-line treatments for advanced unresectable oesophageal squamous cell cancer. A Bayesian network meta-analysis was used to assess clinical outcomes.

RESULTS

Nine studies including 4499 patients receiving first-line treatments were analysed. For all populations, toripalimab plus chemotherapy tended to provide the best overall survival (hazard ratio 0.58, 95% confidence intervals 0.43-0.78) and sintilimab plus chemotherapy provided the best progression-free survival (0.56, 0.46-0.68). Nivolumab plus chemotherapy presented the best objective response rate (odds ratio 2.45, 1.78-3.42) and camrelizumab plus chemotherapy (0.47, 0.29-0.74) appeared to be the safest. Sintilimab plus chemotherapy (0.55, 0.40-0.75) and nivolumab (0.54, 0.37-0.80) plus chemotherapy had the best overall survival in programmed death ligand 1 (PD-L1) tumour proportion score <1% and ≥1% subgroups. Toripalimab plus chemotherapy (0.61, 0.40-0.93) and pembrolizumab (0.57, 0.43-0.75) were the best in overall survival in combined positive score <10 and ≥10 subgroups, respectively. Toripalimab plus chemotherapy showed the best overall survival in the Asian group; pembrolizumab presented better overall survival in the Asian population than the non-Asian group.

CONCLUSION

Most immunotherapy combined with chemotherapy showed superior clinical benefits and sintilimab plus chemotherapy, toripalimab plus chemotherapy and tislelizumab plus chemotherapy had better comprehensive clinical efficacy. PD-L1 expression detection and ethnicity differences are still of great significance and most suitable regimens varied from each subgroup.

Cytomegalovirus Infection and Alzheimer's Disease: A Meta-Analysis

BACKGROUND

Evidence on the association of cytomegalovirus (CMV) infection with Alzheimer's disease (AD) is scarce and the results are inconsistent.

OBJECTIVE

To investigate the association of CMV infection with the risk of AD.

METHODS

Observational studies on the relationship between CMV infection and AD were identified from PubMed, Embase, Web of Science, and the Cochrane Library until September 30, 2022. The quality of included studies was assessed using the Newcastle-Ottawa Scale. Random-effect meta-analysis was performed using a generic inverse-variance method, followed by sensitivity analyses and subgroup analyses based on study designs, regions, adjustments, and population types.

RESULTS

Our search yielded 870 articles, of which 200 were duplicates and 663 did not meet the inclusion criteria, and finally yielded seven studies with 6,772 participants. No strong evidence was observed in the summary analysis for the association of CMV infection and risk of AD (odds ratio [OR] = 1.33; 95% confidence interval [CI]: 0.88, 2.03, I2 =69.9%). However, subgroup analysis showed that an increased risk of AD was detected in East Asians (OR = 2.39; 95% CI: 1.63, 3.50, I2 = 0.00%), cohort studies (OR = 1.99; 95% CI: 1.35, 2.94, I2 = 28.20%), and studies with confounder adjustment (OR = 2.05; 95% CI: 1.52, 2.77, I2 = 0.00%).

CONCLUSIONS

This meta-analysis provides evidence to support the heterogeneity of the associations between CMV infection and AD. Future studies with larger sample sizes and multi-ethnic populations are necessary.

Proportion of participants with type 2 diabetes achieving a metabolic composite endpoint with once-weekly semaglutide treatment versus comparators: Post hoc pooled analysis from SUSTAIN 1-5, 7-10 and SUSTAIN China

AIM

To compare the proportion of participants with type 2 diabetes (T2D) treated with once-weekly (OW) subcutaneous (SC) semaglutide versus comparators who achieved a composite metabolic endpoint.

MATERIALS AND METHODS

SUSTAIN 1-5, 7-10 and SUSTAIN China trial data were pooled. Participants with T2D (aged ≥18 years) and glycated haemoglobin ≥7.0% (≥53 mmol/mol) who had been randomized to OW SC semaglutide (0.5 or 1.0 mg) or comparator in addition to background medication. Using patient-level data pooled by treatment, proportions of participants achieving the metabolic composite endpoint, defined as glycated haemoglobin <7% (<53 mmol/mol), blood pressure <140/90 mmHg and non-high-density lipoprotein cholesterol <130 mg/dl (<3.37 mmol/L), were evaluated following baseline adjustments. Endpoints were analysed per trial using a binomial logistic regression model with treatment, region/country and stratification factor as fixed effects and baseline value as covariate. Pooled analysis used logistic regression with treatment and trial as fixed effects and baseline value as covariate.

RESULTS

This post hoc analysis included data from 7633 participants across 10 trials. The proportion of participants who achieved the metabolic composite endpoint was significantly higher with OW SC semaglutide 0.5 and 1.0 mg versus comparators (23.7% and 32.0% vs. 11.5%, respectively; p < .0001). Likewise, when the OW SC semaglutide doses were pooled, significantly higher proportions of patients receiving semaglutide achieved the composite metabolic endpoint versus comparators (29.1% vs. 11.4%, respectively; p < .0001).

CONCLUSIONS

Treatment with OW SC semaglutide versus comparators was associated with increased proportions of participants with T2D meeting the composite metabolic endpoint.

On committor functions in milestoning

As an optimal one-dimensional reaction coordinate, the committor function not only describes the probability of a trajectory initiated at a phase space point first reaching the product state before reaching the reactant state but also preserves the kinetics when utilized to run a reduced dynamics model. However, calculating the committor function in high-dimensional systems poses significant challenges. In this paper, within the framework of milestoning, exact expressions for committor functions at two levels of coarse graining are given, including committor functions of phase space point to point (CFPP) and milestone to milestone (CFMM). When combined with transition kernels obtained from trajectory analysis, these expressions can be utilized to accurately and efficiently compute the committor functions. Furthermore, based on the calculated committor functions, an adaptive algorithm is developed to gradually refine the transition state region. Finally, two model examples are employed to assess the accuracy of these different formulations of committor functions.

[Enlightenment of World Health Organization fungal priority pathogens list]

The WHO established the first fungal priority pathogens list (FPPL) in October 2022 to focus on and promote further research and policy interventions to strengthen the global response to fungal infections and antifungal resistance. The FPPL and its formulation process provide new significant insights for managing pathogenic fungi and invasive fungal disease (IFD) in China, necessitating the following key actions: Strengthen public health interventions for IFD. Further, it improves the ability of laboratory testing and clinical supervision for IFD and pathogenic fungi. Increase targeted investment and support for innovative research and development in IFD diagnosis, treatment, and prevention.

[Analysis of public health risks associated with pathogenic fungi in China]

At present, the public health risks caused by pathogenic fungi are greater in China and have attracted great attention from disease control departments. Due to the difficulty in diagnosing fungal infections, the public health risk of pathogenic fungi is currently hidden in the unexplained pneumonia/encephalitis/fever syndrome and is not effectively appreciated. From the public health perspective, the mainly focused fungal pathogens include highly pathogenic fungi (including dimorphic fungi and dematiaceous fungi), pathogenic fungi that cause regional aggregation infections, and drug-resistant pathogenic fungi. However, due to the lack of systematic monitoring data, the disease burden related to pathogenic fungi cannot be accurately quantified and evaluated. Therefore, to effectively reduce the serious harm of fungal infections to the public, systematic monitoring of pathogenic fungi should be carried out nationally.

A comparison of size exclusion chromatography-based tandem strategies for plasma exosome enrichment and proteomic analysis

Proteomic analysis of exosomes from human plasma faces a tremendous challenge mainly due to the low abundance of the exosome itself and the complexity of the plasma matrix. Therefore, enrichment of exosomes from human plasma is an essential and indispensable step for large scale and in depth proteomic analysis. Size exclusion chromatography (SEC) is one of the most extensively used methods for exosome isolation from human plasma and many SEC-based tandem methods were established in order to increase the purity of the enriched exosomes and thus the accuracy of the proteomic analysis. To compare the advantages and disadvantages of the different isolation methods and subsequently to promote the establishment of a standardized method for plasma proteomic research, the capacities of the direct SEC method, the combination of SEC with ultracentrifugation (SEC-UC), ultrafiltration (SEC-UF), and titanium dioxide microspheres (SEC-TiO2) were systematically evaluated for exosome isolation from human plasma and thus proteomic analysis. The results demonstrated that the SEC-based tandem methods were superior to the direct SEC method in the purity of exosomes isolated from human plasma. Additionally, the SEC-UC method possessed the highest number of the total identified proteins and the overlapped proteins with the top 100 exosome markers in comparison with the other methods. The SEC-TiO2 method displayed the biggest capacity for plasma protein deleting. We expect that the research will have more beneficial values in the field of exosome research.

When do tripdoublet states fluoresce? A theoretical study of copper(II) porphyrin

Open-shell molecules rarely fluoresce, due to their typically faster non-radiative relaxation rates compared to closed-shell ones. Even rarer is the fluorescence from states that have two more unpaired electrons than the open-shell ground state, since they involve excitations from closed-shell orbitals to vacant-shell orbitals, which are typically higher in energy compared to excitations from or out of open-shell orbitals. States that are dominated by the former type of excitations are known as tripdoublet states when they can be described as a triplet excitation antiferromagnetically coupled to a doublet state, and their description by unrestricted single-reference methods (e.g., U-TDDFT) is notoriously inaccurate due to large spin contamination. In this work, we applied our spin-adapted TDDFT method, X-TDDFT, and the efficient and accurate static-dynamic-static second order perturbation theory (SDSPT2), to the study of the excited states as well as their relaxation pathways of copper(II) porphyrin; previous experimental works suggested that the photoluminescence of some substituted copper(II) porphyrins originate from a tripdoublet state, formed by a triplet ligand π → π* excitation antiferromagnetically coupled with the unpaired d electron. Our results demonstrated favorable agreement between the X-TDDFT, SDSPT2 and experimental excitation energies, and revealed noticeable improvements of X-TDDFT compared to U-TDDFT, not only for vertical excitation energies but also for adiabatic energy differences. These suggest that X-TDDFT is a reliable tool for the study of tripdoublet state fluorescence. Intriguingly, we showed that the aforementioned tripdoublet state is only slightly above the lowest doublet excited state and lies only slightly higher than the lowest quartet state, which suggests that the tripdoublet of copper(II) porphyrin is long-lived enough to fluoresce due to a lack of efficient non-radiative relaxation pathways; an explanation for this unusual state ordering is given. Indeed, thermal vibration correlation function (TVCF)-based calculations of internal conversion, intersystem crossing, and radiative transition rates confirm that copper(II) porphyrin emits thermally activated delayed fluorescence (TADF) and a small amount of phosphorescence at low temperature (83 K), in accordance with experiment. The present contribution is concluded by a few possible approaches of designing new molecules that fluoresce from tripdoublet states.

Triple-negative breast cancer: predictive model of early recurrence based on MRI features

AIM

To develop an integrated model based on preoperative magnetic resonance imaging (MRI) features for predicting early recurrence in patients with triple-negative breast cancer (TNBC).

MATERIALS AND METHODS

Women with TNBC who underwent breast MRI and surgery between 2009 and 2019 were evaluated retrospectively. Two breast radiologists reviewed MRI images independently based on the Breast Imaging Reporting and Data System Lexicon (BI-RADS), and classified the breast oedema scores on T2-weighted imaging (WI) as no oedema, peritumoural oedema, prepectoral oedema, or subcutaneous oedema. The relationship between disease-free survival (DFS) and MRI features was analysed by Cox regression, and a nomogram model was generated based on the results.

RESULTS

150 patients with TNBC were included and divided into a training cohort (n=78) and validation cohort (n=72). MRI features including subcutaneous oedema and rim enhancement showed a tendency to worsen DFS in univariate analysis. Multivariate analysis showed that subcutaneous oedema (p=0.049, HR [95% confidence interval {CI} = 8.24 [1.01-67.52]) and rim enhancement (p=0.016, HR [95% CI] = 4.38 [1.32-14.54]) were independent predictors for DFS. In the nomogram, the areas under the curves (AUCs) of the training cohort was 0.808, and that of the validation cohort was 0.875.

CONCLUSION

The presence of subcutaneous oedema or rim enhancement on preoperative breast MRI was shown to be a good predictor of poor survival outcomes in patients with TNBC.

[Report content and prenatal diagnosis of non-invasive prenatal testing for sex chromosome aneuploidy]

Objective: To analyze the report content, the methods and results of prenatal diagnosis of high risk of sex chromosome aneuploidy (SCA) in non-invasive prenatal testing (NIPT). Methods: A total of 227 single pregnancy pregnant women who received genetic counseling and invasive prenatal diagnosis at Drum Tower Hospital Affiliated to the Medical School of Nanjing University from January 2015 to April 2022 due to the high risk of SCA suggested by NIPT were collected. The methods and results of prenatal diagnosis were retrospectively analyzed, and the results of chromosome karyotype analysis and chromosome microarray analysis (CMA) were compared. The relationship between NIPT screening and invasive prenatal diagnosis was analyzed. Results: (1) Prenatal diagnosis methods for 277 SCA high risk pregnant women included 73 cases of karyotyping, 41 cases of CMA and 163 cases of karyotyping combined with CMA, of which one case conducted amniocentesis secondly for further fluorescence in situ hybridization (FISH) testing. Results of invasive prenatal diagnosis were normal in 166 cases (59.9%, 166/277), and the abnormal results including one case of 45,X (0.4%, 1/277), 18 cases of 47,XXX (6.5%, 18/277), 36 cases of 47,XXY (13.0%, 36/277), 20 cases of 47,XYY (7.2%, 20/277), 1 case of 48,XXXX (0.4%, 1/277), 20 cases of mosaic SCA (7.2%, 20/277), 5 cases of sex chromosome structural abnormality or large segment abnormality (1.8%, 5/277), and 10 cases of other abnormalities [3.6%, 10/277; including 9 cases of copy number variation (CNV) and 1 case of balanced translocation]. Positive predictive value (PPV) for SCA screening by NIPT was 34.7% (96/277). (2) Among the 163 cases tested by karyotyping combined with CMA, 11 cases (6.7%, 11/163) showed inconsistent results by both methods, including 5 cases of mosaic SCA, 1 case of additional balanced translocation detected by karyotyping and 5 cases of additional CNV detected by CMA. (3) NIPT screening reports included 149 cases of "sex chromosome aneuploidy"(53.8%, 149/277), 54 cases of "number of sex chromosome increased" (19.5%, 54/277), and 74 cases of "number of sex chromosome or X chromosome decreased" (26.7%, 74/277). The PPV of "number of sex chromosome increased" and "number of sex chromosome or X chromosome decreased" were 72.2% (39/54) and 18.9% (14/74), respectively, and the difference was statistically significant (χ2=34.56, P<0.01). Conclusions: NIPT could be served as an important prenatal screening technique of SCA, especially for trisomy and mosaicism, but the PPV is comparatively low. More information of NIPT such as the specific SCA or maternal SCA might help improving the confidence of genetic counseling and thus guide clinic management. Multi technology platforms including karyotyping, CMA and FISH could be considered in the diagnosis of high risk of SCA by NIPT.

[Research advances on application of pancreatic stone protein in the early diagnosis of sepsis]

Sepsis is a severe life-threatening syndrome characterized by an abnormal host response to infection that can rapidly evolve into septic shock and multiple organ failure. Treatment of sepsis depends on early identification and diagnosis as well as adequate and timely anti-infection and multi-organ functional support. In recent years, pancreatic stone protein has been widely studied as a new biomarker for sepsis. Existing evidence shows that compared with the commonly used inflammatory markers in clinical practice, pancreatic stone protein has higher sensitivity and specificity in the diagnosis of sepsis. It enables the early diagnosis of sepsis and assessment of the severity of septic patients to a certain extent. This article reviews the characteristics, biological functions, diagnostic features, and clinical application of pancreatic stone protein.

Measurement of Ultra-High-Energy Diffuse Gamma-Ray Emission of the Galactic Plane from 10 TeV to 1 PeV with LHAASO-KM2A

The diffuse Galactic γ-ray emission, mainly produced via interactions between cosmic rays and the interstellar medium and/or radiation field, is a very important probe of the distribution, propagation, and interaction of cosmic rays in the Milky Way. In this Letter, we report the measurements of diffuse γ rays from the Galactic plane between 10 TeV and 1 PeV energies, with the square kilometer array of the Large High Altitude Air Shower Observatory (LHAASO). Diffuse emissions from the inner (15°10  TeV). The energy spectrum in the inner Galaxy regions can be described by a power-law function with an index of -2.99±0.04, which is different from the curved spectrum as expected from hadronic interactions between locally measured cosmic rays and the line-of-sight integrated gas content. Furthermore, the measured flux is higher by a factor of ∼3 than the prediction. A similar spectrum with an index of -2.99±0.07 is found in the outer Galaxy region, and the absolute flux for 10≲E≲60  TeV is again higher than the prediction for hadronic cosmic ray interactions. The latitude distributions of the diffuse emission are consistent with the gas distribution, while the longitude distributions show clear deviation from the gas distribution. The LHAASO measurements imply that either additional emission sources exist or cosmic ray intensities have spatial variations.

SOiCISCF: Combining SOiCI and iCISCF for Variational Treatment of Spin-Orbit Coupling

It has recently been shown that the SOiCI approach [Zhang, N.; J. Phys.: Condens. Matter 2022, 34, 224007], in conjunction with the spin-separated exact two-component relativistic Hamiltonian, can provide very accurate fine structures of systems containing heavy elements by treating electron correlation and spin-orbit coupling (SOC) on an equal footing. Nonetheless, orbital relaxations/polarizations induced by SOC are not yet fully accounted for due to the use of scalar relativistic orbitals. This issue can be resolved by further optimizing the still real-valued orbitals self-consistently in the presence of SOC, as done in the spin-orbit coupled CASSCF approach [Ganyushin, D.; et al. J. Chem. Phys. 2013, 138, 104113] but with the iCISCF algorithm [Guo, Y.; J. Chem. Theory Comput. 2021, 17, 7545-7561] for large active spaces. The resulting SOiCISCF employs both double group and time reversal symmetries for computational efficiency and the assignment of target states. The fine structures of p-block elements are taken as showcases to reveal the efficacy of SOiCISCF.

Approximating First Hitting Point Distribution in Milestoning for Rare Event Kinetics

Milestoning is an efficient method for rare event kinetics calculation using short trajectory parallelization. Mean first passage time (MFPT) is the key kinetic output of Milestoning, whose accuracy crucially depends on the initial distribution of the short trajectory ensemble. The true initial distribution, i.e., the first hitting point distribution (FHPD), has no analytic expression in the general case. Here, we introduce two algorithms, local passage time weighted Milestoning (LPT-M) and Bayesian inference Milestoning (BI-M), to accurately and efficiently approximate FHPD for systems at equilibrium condition. Starting from sampling the Boltzmann distribution on milestones, we calculate the proper weighting factor for the short trajectory ensemble. The methods are tested on two model examples for illustration purpose. Both methods improve significantly over the widely used classical Milestoning (CM) method in terms of the accuracy of MFPT. In particular, BI-M covers the directional Milestoning method as a special case in deterministic Hamiltonian dynamics. LPT-M is especially advantageous in terms of computational costs and robustness with respect to the increasing number of intermediate milestones. Furthermore, a locally iterative correction algorithm for nonequilibrium stationary FHPD is developed for exact MFPT calculation, which can be combined with LPT-M/BI-M and is much cheaper than the exact Milestoning (ExM) method.

"It just made me feel better": qualitative examination of the implementation of a novel virtual psychosocial support program for adolescents with cancer

PURPOSE

Adolescents with cancer routinely report feelings of isolation and exclusion, including from medical decision-making. To address this problem and support adolescents, we designed and implemented the novel, virtual, weekly Teens4Teens peer support group and patient education program. We examined the views of participating adolescents, program guest speakers, and program moderators as they pertained to the need for the program, its feasibility, acceptability, and perceived impact.

METHODS

We recruited all available adolescents, moderators, and guest speakers who participated in Teens4Teens to take part in audio-recorded, semi-structured interviews. Interviews were transcribed, coded, and analyzed using thematic analysis.

RESULTS

We conducted 21 interviews across participant groups. We identified four broad themes: pathways into the Teen4Teens program, Teens4Teens implementation capacity, perspectives of the positive impact of Teens4Teens, and suggestions to improve Teens4Teens. These themes described a perceived need for adolescent-centered psychosocial programming in pediatric cancer care, provided lessons on how best to build and apply such a program, and highlighted the value of the program for both adolescents' and clinicians' acceptability, feasibility, and perceived utility.

CONCLUSION

Adolescents, guest speakers, and moderators valued Teens4Teens and made suggestions to improve capacity to routinely implement the program. Adolescent-tailored psychosocial programming, such as Teens4Teens, is positioned to be integrated into clinical care with relative ease and may serve to improve the cancer care experience of adolescents and their families. This study has potential to provide researchers and clinicians with valuable information about the content, design, and delivery of virtual peer support programming for adolescents with cancer.

Dose Painting Radiotherapy Guided by Diffusion-Weighted Magnetic Resonance vs. 18F-FDG-PET/CT in Locoregionally Advanced Nasopharyngeal Carcinoma: A Randomized, Controlled Clinical Trial

PURPOSE/OBJECTIVE(S)

This phase II randomized controlled trial aimed at comparing the efficacy and toxicity of diffusion-weighted magnetic resonance imaging (DWI)-guided dose painting radiotherapy (DP-RT), FDG-PET/CT-guided DP-RT, and conventional MRI-based radiotherapy (RT) in locoregionally advanced nasopharyngeal carcinoma (NPC).

MATERIALS/METHODS

A total of 330 patients with stage III-IVa NPC disease were randomly assigned in a 1:1:1 ratio to receive induction chemotherapy followed by concurrent chemoradiotherapy by DWI-guided DP-RT (group A, n = 110), FDG-PET/CT-guided DP-RT (group B, n = 110), or conventional MRI-based RT (group C, n = 110). All patients received volumetric modulated arc therapy (VMAT). In group A, subvolume GTVnx-DWI (gross tumor volume of nasopharynx in DWI) was defined as the areas within the GTVnx (gross tumor volume of nasopharynx) with an apparent diffusion coefficient (ADC) below the mean ADC (ADC < mean). In group B, subvolume GTVnx-PET (gross tumor volume of nasopharynx in PET images) was defined within GTVnx as the SUV50%max isocontour. The doses to GTVnx-DWI in group A and GTVnx-PET in group B were escalated to 75.2 Gy/32 fx in patients with T1-2 disease and to 77.55 Gy/33 fx in those with T3-4 disease in 2.35 Gy per fraction. In group C, planning gross tumor volume of nasopharynx (PGTVnx) was irradiated at 70.4 to 72.6 Gy/32 to 33 fx in 2.2 Gy per fraction. This trial is registered with chictr.org.cn (ChiCTR2200057476).

RESULTS

Group A and B showed significant higher complete response (CR) rates than group C (100%, 100%, and 96.4% for group A, B and C, respectively, p = 0.036). In groups A, B and C, the 1-year local recurrence-free survival (LRFS) rates were 100%, 100%, and 94.5%, respectively (p = 0.002). The 1-year disease-free survival (DFS) rates were 100%, 99.1%, and 92.7%, respectively (p = 0.001). The 1-year distant metastasis-free survival (DMFS) rates were 100%, 99.1%, and 93.6%, respectively (p = 0.004). The 1-year overall survival (OS) rates were 100%, 100%, and 95.4%, respectively (p = 0.006). Group A and B had significantly higher 1-year LRFS, DFS, DMFS, and OS than those in group C. No significant differences were observed in LRFS, DFS, DMFS and OS between group A and B. Group B (PET/CT group) had a higher incidence of grade 3-4 acute ototoxicity (3.6%) than group A (0%) and group C (0%, p = 0.036). No significant differences in other grade 3-4 acute adverse events and late toxic effects were observed among the three groups, and no patient had grade 5 toxicities. Multivariate analysis showed that dose painting (DWI-guided DP-RT and PET/CT-guided DP-RT vs conventional MRI-based RT) was associated with improved LRFS, DFS, DMFS and OS.

CONCLUSION

Both DWI-guided DP-RT and PET/CT-guided DP-RT plus chemotherapy are associated with improved LRFS, DFS, DMFS and OS compared with conventional MRI-based RT among patients with locoregionally advanced NPC. DWI-guided DP-RT does not increase toxicities, but PET/CT-guided DP-RT has higher incidence of acute ototoxicity.

Improving Dose Volume Histogram (DVH) Based Analysis of Clinical Outcomes Using Modern Statistical Techniques: A Systematic Answer to Multiple Comparisons Concerns

PURPOSE/OBJECTIVE(S)

DVH constraints are essential in the clinical practice of radiation therapy. Historically, DVH constraints were found through sparse sampling of all possible DVH indices to find one that appeared to be most predictive for clinical toxicity. This approach can lead to inconsistent results among studies and to multiple comparison concerns. We aim to solve both problems by examining a full array of DVH indices using statistical methods that account for strong correlations among DVH indices and incorporate radiobiological knowledge constraints.

MATERIALS/METHODS

We extracted a dense array of V%_D indices from a treatment planning system using ESAPI interface, with V%_D corresponding to the volume fraction irradiated to dose D, or higher. We used Fused Lasso as the base model to compensate for correlations among DVH indices because it applies a penalty on the difference between DVH variables with adjacent dose. The base model was augmented with additional constraints based on radiobiological considerations: the positivity constraint (beta_i > 0) which assumes that any tissue irradiation cannot reduce the risk of toxicity, and monotonicity constraint (beta_i+1 > = beta_i) which assumes that higher dose to a fixed volume fraction cannot be associated with a lower risk of toxicity. We called the hybrid model KC-Lasso (Knowledge Constrained Lasso) and applied it to two clinical examples: grade 2 acute rectal toxicity in conventionally fractionated RT for 79 prostate cancer patients (77.4 Gy + MR based boost to 81-83 Gy) and cardiac toxicity in conventionally fractionated RT for 119 locally advanced Non-small Cell Lung Cancer (NSCLC) patients (Median prescribed dose 62 Gy). We further examined alternative data driven models to determine the importance of knowledge constraints.

RESULTS

KC-Lasso detected two distinct dose thresholds for grade 2 rectal toxicity, at 35 Gy and 78 Gy. A threshold of 51 Gy was detected for reduced overall survival due to cardiac irradiation in NSCLC patients. An examination of KC-Lasso models at varying step size suggested that a single mid-range index can be used as a treatment planning constraint while full model can be used for confirmatory, final plan evaluation. Alternative models which lack knowledge constraints show patterns of negative and isolated coefficients which are difficult to interpret and are not likely to be generalizable.

CONCLUSION

A more systematic approach to the analysis of correlations between DVH constraints and clinical toxicity can lead to greater consistency of results among different studies, better understanding of true dose thresholds and results which are more generalizable.

Reinforcement Learning Powered Station Parameter Optimized Radiation Therapy (SPORT): A Novel Treatment Planning and Beam Delivery Technique

PURPOSE/OBJECTIVE(S)

Conventional intensity modulated radiation therapy (IMRT) with a typical 5-20 fixed beams often does not provide sufficient angular sampling required for conformal dose shaping, whereas current volumetric modulated arc therapy (VMAT) discretizes the angular space into equally spaced control points without considering the differential need for intensity modulation of different angles, leading to undersampling at some angles while oversampling at some other angles. Our goal is to develop a node or station parameter optimized radiation therapy (SPORT) strategy with simultaneously optimized angular sampling and beam modulation by leveraging state-of-the-art reinforcement learning and the unique capability of modern digital LINACs in dose delivery through programmable nodal points.

MATERIALS/METHODS

We developed a SPORT optimization framework, in which, the process of programming control points (or station parameters) was formulated as a stochastic dynamic programming problem, which was solved by a reinforcement learning-based algorithm. On-policy reinforcement learning method, namely, state-action-reward-state-action (SARSA) was integrated with deep convolutional neural network to predict station parameters by utilizing the patient's anatomical structures meanwhile considering the delivery capability of a typical digital LINAC machine. Here, the deep convolutional neural network estimated the state-action value by using the quality of the plan with current station parameters when a next potential station parameter was selected. The state-action value was then updated by SARSA learning. The quality of the plan was quantified by dosimetry constraints. The model was assessed by a retrospective study on a cohort of patients underwent head-and-neck radiation therapy. Dosimetric analysis and delivery efficiency comparisons were used to evaluate the performance of the proposed framework.

RESULTS

Our model was used to generate 16 plans unseen in the original training set. All the plans predicted by our model achieved better dose distributions without violating clinical planning constraints. Moreover, instead of using 4 full standard arcs in the original clinically used plans obtained via manual optimization, the predicted plans only used one full standard arc (about 178 control points) plus boost from a few sub-arcs (less than 30 degrees of gantry angles), which significantly improved the efficiency of the beam delivery. We are in the process of integrating the sub-arcs into the full arc by considering the programmable capability of modern LINACs.

CONCLUSION

We demonstrated that a machine learning-based SPORT framework capable of optimizing the spatial sampling and beam modulation simultaneously for modern radiation therapy. The framework not only significantly improves the quality and efficiency of beam delivery, but also has the potential to be incorporated into current clinical workflow to improve the efficiency of dose planning and delivery.

Patient-Specific 3D CT Images Reconstruction from 2D KV Images Via Vision Transformer-Based Deep-Learning

PURPOSE/OBJECTIVE(S)

In some proton therapy facilities, patient alignment relies on two 2D orthogonal kV images, taken at fixed, oblique angles, as no 3D on-the-bed-imaging is available. The visibility of the tumor in kV images is limited since the patient's 3D anatomy is projected onto a 2D plane, especially when the tumor is behind a high-density structure such as bone. This can lead to a large patient setup error. A solution to this problem is to reconstruct the 3D CT image from the kV images obtained in the treatment position.

MATERIALS/METHODS

An asymmetric autoencoder-like network built with vision-transformer blocks was developed. The data was collected from a head and neck patient: 2 orthogonal kV images (1024X1024 voxels), 1 3D CT with padding (512X512X512) acquired from the in-room CT-on-rails before kVs were taken and 2 digitally-reconstructed-radiograph (DRR) images (512X512) based on the CT. We resampled kV images every 8 voxels and DRR and CT every 4 voxels, thus formed a dataset consisting of 262,144 samples, in which the images had a dimension of 128 for each direction. The value of each voxel in CT was normalized to range 0-1 with a uniform shift of 1000 and a denominator of 4000. For kV and DRR, we ranked all voxels value in an ascending order and normalized the values of the first 80% voxels to range 0-0.8 and the rest to range 0.8-1, thus yielding a quasi-Gaussian distribution, which was favorable by the deep neural networks. We further cropped kV and DRR images with a self-supervised bitmap based on the voxels' gradients. In training, both kV and DRR were utilized, and the encoder was encouraged to learn the same feature maps for kV images and its corresponding DRR images with mean-absolute-error (MAE) as the similarity loss. Then the decoder would reconstruct the 3D CT image from the feature maps of the kV images with the CT-on-rails as ground-truth (gCT) and MAE as the reconstruction loss. In testing, only independent kV images were used. The full-size synthetic CT (sCT) was achieved by concatenating the sCTs generated by the model according to their spatial information. The image quality of the sCT was evaluated using MAE and per-voxel-absolute-CT-number-difference volume histogram (CDVH). The proposed network was implemented with PyTorch deep learning library and both distributed data parallel (DDP) and automatic mixed precision (AMP) were applied to saving memory and accelerating the training speed. We used the AdamW optimizer with β1 = 0.9 and β2 = 0.999 and a cosine annealing learning rate scheduler with an initial learning of 1e-7 and 20 warm-up epochs.

RESULTS

The model achieved a MAE of <40HU and the CDVH showed that <5% of the voxels had a per-voxel-absolute-CT-number-difference larger than 185HU. The profile of a typical gCT slice and its corresponding sCT slice exhibited a high agreement, indicating the high similarity between the gCT and sCT.

CONCLUSION

A patient-specific vision-transformer-based network was developed and shown to be accurate and efficient to reconstruct 3D CT images from kV images.