Calculation of solvation force in molecular dynamics simulation by deep-learning method.

Electrostatic calculations are generally used in studying the thermodynamics and kinetics of biomolecules in solvent. Generally, this is performed by solving the Poisson-Boltzmann equation on a large grid system, a process known to be time consuming. In this study, we developed a deep neural network to predict the decomposed solvation free energies and forces of all atoms in a molecule. To train the network, the internal coordinates of the molecule were used as the input data, and the solvation free energies along with transformed atomic forces from the Poisson-Boltzmann equation were used as labels. Both the training and prediction tasks were accelerated on GPU. Formal tests demonstrated that our method can provide reasonable predictions for small molecules when the network is well-trained with its simulation data. This method is suitable for processing lots of snapshots of molecules in a long trajectory. Moreover, we applied this method in the molecular dynamics simulation with enhanced sampling. The calculated free energy landscape closely resembled that obtained from explicit solvent simulations.

Hierarchical MOFs with Good Catalytic Properties and Structural Stability in Oxygen-Rich and High-Temperature Environments.

Metal-organic framework materials are ideal materials characterized by open frameworks, adjustable components, and high catalytic activity. They are extensively utilized for catalysis. Due to decomposition and structural collapse under high temperatures and an oxygen-rich environment, the potential of thermal catalysis is greatly limited. In this research, Co-rich hollow spheres (Co-HSs) with a gradient composition are designed and synthesized to investigate their thermal catalytic properties in the ammonium perchlorate（AP）system. The results demonstrate that Co-HSs@AP exhibits good thermal catalytic activity and a high-temperature decomposition of 292.5 °C, which is 121.6 °C lower than pure AP. The hierarchical structure confers structural stability during the thermal decomposition process. Thermogravimetry-infrared indicates that the inclusion of Co-HSs successfully boosts the level of reactive oxygen species and achieves thorough oxidation of NH3. Based on the above phenomenon, macro dynamics calculations are carried out. The results show that Co-HSs can promote the circulation of lattice oxygen and reactive oxygen species and the multidimensional diffusion of NH3 in an oxygen-rich environment. This material has significant potential for application in the fields of thermal catalysis and ammonia oxidation.

FLZ13 interacts with FLC and ABI5 to negatively regulate flowering time in Arabidopsis.

The transition from vegetative to reproductive growth, known as flowering, is a critical developmental process in flowering plants to ensure reproductive success. This process is strictly controlled by various internal and external cues; however, the underlying molecular regulatory mechanisms need to be further characterized. Here, we report a plant-specific protein, FCS-LIKE ZINC FINGER PROTEIN 13 (FLZ13), which functions as a hitherto unknown negative modulator of flowering time in Arabidopsis thaliana. Biochemical analysis showed that FLZ13 directly interacts with FLOWERING LOCUS C (FLC), a major flowering repressor, and that FLZ13 largely depends on FLC to repress the transcription of two core flowering integrators: FLOWERING LOCUS T and SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1. In addition, FLZ13 works together with ABSCISIC ACID INSENSITIVE 5 to activate FLC expression to delay flowering. Taken together, our findings suggest that FLZ13 is an important component of the gene regulatory network for flowering time control in plants.

Homozygous deletion of the DSG3 terminal exon associated with acantholytic blistering of the oral and laryngeal mucosa.

We report a novel homozygous 49.6 kb deletion of chromosome 18q12.1 involving the last exon of DSG3 in dizygotic twins with phenotype consistent with acantholytic blistering of the oral and laryngeal mucosa (ABOLM). The twin siblings presented predominantly with friability of the laryngeal and respiratory mucosa. This is only the second report in the literature of this unusual autosomal recessive blistering disorder. The diagnosis explains the mucosal phenotype of a pemphigus-like disorder without evidence of autoimmune dysfunction. The exclusion of an autoimmune basis has management implications. The deletion also involved the DSG2 gene, which is associated with arrhythmogenic right ventricular dysplasia (ARVD). The affected siblings and heterozygous parents do not show any cardiac phenotype at this time. Functional studies would further clarify how deletions resulting in loss of function of DSG3 may cause the reported phenotypes of DSG3-related ABOLM.

MIST: multiple instance learning network based on Swin Transformer for whole slide image classification of colorectal adenomas.

Colorectal adenoma is a recognized precancerous lesion of colorectal cancer (CRC), and at least 80% of colorectal cancers are malignantly transformed from it. Therefore, it is essential to distinguish benign from malignant adenomas in the early screening of colorectal cancer. Many deep learning computational pathology studies based on whole slide images (WSIs) have been proposed. Most approaches require manual annotation of lesion regions on WSIs, which is time-consuming and labor-intensive. This study proposes a new approach, MIST - Multiple Instance learning network based on the Swin Transformer, which can accurately classify colorectal adenoma WSIs only with slide-level labels. MIST uses the Swin Transformer as the backbone to extract features of images through self-supervised contrastive learning and uses a dual-stream multiple instance learning network to predict the class of slides. We trained and validated MIST on 666 WSIs collected from 480 colorectal adenoma patients in the Department of Pathology, The Affiliated Drum Tower Hospital of Nanjing University Medical School. These slides contained six common types of colorectal adenomas. The accuracy of external validation on 273 newly collected WSIs from Nanjing First Hospital was 0.784, which was superior to the existing methods and reached a level comparable to that of the local pathologist's accuracy of 0.806. Finally, we analyzed the interpretability of MIST and observed that the lesion areas of interest in MIST were generally consistent with those of interest to local pathologists. In conclusion, MIST is a low-burden, interpretable, and effective approach that can be used in colorectal cancer screening and may lead to a potential reduction in the mortality of CRC patients by assisting clinicians in the decision-making process. © 2022 The Pathological Society of Great Britain and Ireland.

Highly Localized Surface Plasmon Nanolasers via Strong Coupling.

Surface plasmons have robust and strong confinement to the light field which is beneficial for the light-matter interaction. Surface plasmon amplification by stimulated emission of radiation (SPACER) has the potential to be integrated on the semiconductor chip as a compact coherent light source, which can play an important role in further extension of Moore's law. In this study, we demonstrate the localized surface plasmon lasing at room temperature in the communication band using metallic nanoholes as the plasmonic nanocavity and InP nanowires as the gain medium. Optimizing laser performance has been demonstrated by coupling between two metallic nanoholes which adds another degree of freedom for manipulating the lasing properties. Our plasmonic nanolasers exhibit lower power consumption, smaller mode volumes, and higher spontaneous emission coupling factors due to enhanced light-matter interactions, which are very promising in the applications of high-density sensing and photonic integrated circuits.

[Effect of Naotaifang on microglial polarization and glial scar following cerebral ischemia reperfusion injury].

This study aims to investigate the effect of Naotaifang(NTF) on the proteins associated with microglial polarization and glial scar in the rat model of cerebral ischemia reperfusion injury(CIRI). The CIRI model was established by middle cerebral artery occlusion/reperfusion. The 48 successfully modeled rats were randomized into model 7 d, model 14 d, NTF 7 d, and NTF 14 d groups(n=12). In addition, 12 SD rats were selected as the sham group. The NTF group was administrated with NTF suspension at 27 g·kg~(-1)·d~(-1) by gavage, and the sham, model 7 d, and model 14 d groups were administrated with the same volume of normal saline every day by gavage for 7 and 14 days, respectively. After the intervention, Longa score was evaluated. The infarct volume was measured by 2,3,5-triphenyl-2H-tetrazolium chloride(TTC) staining. Morris water maze and open field tests were carried out to evaluate the spatial learning, memory, cognitive function, and anxiety degree of rats. Hematoxylin-eosin(HE) staining was employed to observe the morphological structure and damage of the brain tissue. The immunofluorescence assay was employed to measure the expression of glial fibrillary acidic protein(GFAP) and glial scar. Western blot was employed to determine the protein levels of GFAP, neurocan, phosphacan, CD206, arginase-1(Arg-1), interleukin(IL)-1ß, IL-6, and IL-4. Compared with the sham, model 7 d and model 14 d groups showed cerebral infarction of different degrees, severe pathological injury of cerebral cortex and hippocampus, neurological impairment, reduced spatial learning and memory, cognitive dysfunction, severe anxiety, astrocyte hyperplasia, thickening penumbra glial scar, and up-regulated protein levels of IL-1ß, IL-6, GFAP, neurocan, phosphacan, CD206, and Arg-1(P<0.01). Compared with the model group, NTF 7 d and NTF 14 d groups improved spatial learning, memory, and cognitive function, reduced anxiety, improved nerve function, reduced cerebral infarction volume, reduced astrocyte hyperplasia, thinned penumbra glial scar, down-regulated the protein levels of GFAP, neurocan, phosphacan, IL-6, and IL-1ß, and up-regulated the protein levels of IL-4, CD206, and Arg-1(P<0.05 or P<0.01). NTF exerts a neuroprotective effect on CIRI by inducing the M2 polarization of microglia, inhibiting inflammatory response, and reducing the formation of glial scar.

The role of regulatory T cells in the pathogenesis of acute kidney injury.

The incidence of acute kidney injury (AKI) is on the rise and is associated with high mortality; however, there are currently few effective treatments. Moreover, the relationship between Tregs and other components of the immune microenvironment (IME) in the pathogenesis of AKI remains unclear. We downloaded four publicly accessible AKI datasets, GSE61739, GSE67401, GSE19130, GSE81741, GSE19288 and GSE106993 from the gene expression omnibus (GEO) database. Additionally, we gathered two kidney single-cell sequencing (scRNA-seq) samples from the Department of Organ Transplantation at Zhujiang Hospital of Southern Medical University to investigate chronic kidney transplant rejection (CKTR). Moreover, we also collected three samples of normal kidney tissue from GSE131685. By analysing the differences in immune cells between the AKI and Non-AKI groups, we discovered that the Non-AKI group contained a significantly greater number of Tregs than the AKI group. Additionally, the activation of signalling pathways, such as inflammatory molecules secretion, immune response, glycolytic metabolism, NOTCH, FGF, NF-κB and TLR4, was significantly greater in the AKI group than in the Non-AKI group. Additionally, analysis of single-cell sequencing data revealed that Tregs in patients with chronic kidney rejection and in normal kidney tissue have distinct biology, including immune activation, cytokine production, and activation fractions of signalling pathways such as NOTCH and TLR4. In this study, we found significant differences in the IME between AKI and Non-AKI, including differences in Tregs cells and activation levels of biologically significant signalling pathways. Tregs were associated with lower activity of signalling pathways such as inflammatory response, inflammatory molecule secretion, immune activation, glycolysis.

Near-Infrared II Hyperspectral Imaging Improves the Accuracy of Pathological Sampling of Multiple Cancer Types.

Pathological histology is the "gold standard" for clinical diagnosis of cancer. Incomplete or excessive sampling of the formalin-fixed excised cancer specimen will result in inaccurate histologic assessment or excessive workload. Conventionally, pathologists perform specimen sampling relying on naked-eye observation, which is subjective and limited by human perception. Precise identification of cancer tissue, size, and margin is challenging, especially for lesions with inconspicuous tumors. To overcome the limits of human eye perception (visible: 400-700 nm) and improve the sampling efficiency, in this study, we propose using a second near-infrared window (NIR-II: 900-1700 nm) hyperspectral imaging (HSI) system to assist specimen sampling on the strength of the verified deep anatomical penetration and low scattering characteristics of the NIR-II optical window. We used selected NIR-II HSI narrow bands to synthesize color images for human eye observation and also applied a machine learning-based algorithm on the complete NIR-II HSI data for automatic tissue classification to assist pathologists in specimen sampling. A total of 92 tumor samples were collected, including 7 types. Sixty-two (62/92) samples were used as the validation set. Five experienced pathologists marked the contour of the cancer tissue on conventional color images by using different methods, and compared it with the "gold standard," showing that NIR-II HSI-assisted methods had significant improvements in determining cancer tissue compared with conventional methods (conventional color image with or without X-ray). The proposed system can be easily integrated into the current workflow, with high imaging efficiency and no ionizing radiation. It may also find applications in intraoperative detection of residual lesions and identification of different tissues.

Exploration of immunotherapy in advanced pulmonary lymphoepithelioma-like carcinoma.

Pulmonary lymphoepithelioma-like carcinoma (PLELC) is a rare and histologically distinctive subtype of nonsmall cell lung cancer (NSCLC). High expression of programmed death ligand 1 (PD-L1) and scarcity of druggable driver mutations raise the potential of immunotherapy for advanced PELEC. However, evidence on the clinical impact of immune-checkpoint inhibitors (ICIs) remained limited and unconvincing. The present study retrospectively enrolled advanced PLELC patients who received ICIs either as up-front or salvage therapy in SYSUCC between March 15, 2017 and March 15, 2022. The comparative efficacy of chemoimmunotherapy vs chemotherapy in the first-line setting and chemoimmunotherapy vs ICIs monotherapy in the ≥2 line setting was investigated. A total of 96 patients were finally enrolled; 49 PLELC patients received immunotherapy plus platinum-based chemotherapy, while 45 patients received platinum-based chemotherapy as first-line treatment. Patients with chemoimmunotherapy significantly obtain more survival benefits than those receiving chemotherapy (median progression-free survival [PFS]: 15.6 vs 8.6 months, P = .0015). Additionally, patients with chemoimmunotherapy obtained more PFS benefits than those with ICIs monotherapy in the ≥2 line of therapy (median PFS: 21.7 months vs 7.8 months, P = .094). A significant correlation was observed between prognostic nutritional index (PNI) and favorable treatment outcomes in patients receiving first-line chemoimmunotherapy (median PFS: 17.8 months vs 7.6 months, P < .0001). Likewise, patients in the monocyte-to-lymphocyte ratio (MLR)-high group had significantly shorter PFS than the MLR-low group (median PFS: 11.2 months vs not reached, P = .0009). Our study elucidated the superior efficacy of ICIs therapy, especially chemoimmunotherapy in advanced PLELC, which may provide new insight into the role of immunotherapy in advanced PLELC.

Causal Genetic Variants in Stillbirth.

BACKGROUND: In the majority of cases, the cause of stillbirth remains unknown despite detailed clinical and laboratory evaluation. Approximately 10 to 20% of stillbirths are attributed to chromosomal abnormalities. However, the causal nature of single-nucleotide variants and small insertions and deletions in exomes has been understudied. METHODS: We generated exome sequencing data for 246 stillborn cases and followed established guidelines to identify causal variants in disease-associated genes. These genes included those that have been associated with stillbirth and strong candidate genes. We also evaluated the contribution of 18,653 genes in case-control analyses stratified according to the degree of depletion of functional variation (described here as "intolerance" to variation). RESULTS: We identified molecular diagnoses in 15 of 246 cases of stillbirth (6.1%) involving seven genes that have been implicated in stillbirth and six disease genes that are good candidates for phenotypic expansion. Among the cases we evaluated, we also found an enrichment of loss-of-function variants in genes that are intolerant to such variation in the human population (odds ratio, 2.15; 95% confidence interval [CI], 1.46 to 3.06). Loss-of-function variants in intolerant genes were concentrated in genes that have not been associated with human disease (odds ratio, 2.22; 95% CI, 1.41 to 3.34), findings that differ from those in two postnatal clinical populations that were also evaluated in this study. CONCLUSIONS: Our findings establish the diagnostic utility of clinical exome sequencing to evaluate the role of small genomic changes in stillbirth. The strength of the novel risk signal (as generated through the stratified analysis) was similar to that in known disease genes, which indicates that the genetic cause of stillbirth remains largely unknown. (Funded by the Institute for Genomic Medicine.).

Enhanced sampling in explicit solvent by deep learning module in FSATOOL.

FSATOOL is an integrated molecular simulation and data analysis program. Its old molecular dynamics engine only supports simulations in vacuum or implicit solvent. In this work, we implement the well-known smooth particle mesh Ewald method for simulations in explicit solvent. The new developed engine is runnable on both CPU and GPU. All the existed analysis modules in the program are compatible with the new engine. Moreover, we also build a complete deep learning module in FSATOOL. Based on the module, we further implement two useful trajectory analysis methods: state-free reversible VAMPnets and time-lagged autoencoder. They are good at searching the collective variables related to the conformational transitions of biomolecules. In FSATOOL, these collective variables can be further used to construct a bias potential for the enhanced sampling purpose. We introduce the implementation details of the methods and present their actual performances in FSATOOL by a few enhanced sampling simulations.

Oriented Assembled Prussian Blue Analogue Framework for Confined Catalytic Decomposition of Ammonium Perchlorate.

The design of highly dispersed active sites of hollow materials and unique contact behavior with the components to be catalyzed provide infinite possibilities for exploring the limits of catalyst capacity. In this study, the synthesis strategy of highly open 3-dimensional frame structure Prussian blue analogues (CoFe-PBA) was explored through structure self-transformation, which was jointly guided by template mediated epitaxial growth, restricted assembly and directional assembly. Additionally, good application prospect of CoFe-PBA as combustion catalyst was discussed. The results show that unexpected thermal decomposition behavior can be achieved by limiting AP(ammonium perchlorate) to the framework of CoFe-PBA. The high temperature decomposition stage of AP can be advanced to 283.6 °C and the weight loss rate can reach 390.03% min-1 . In-situ monitoring shows that CoFe-PBA can accelerate the formation of NO and NO2 . The calculation of reaction kinetics proved that catalytic process was realized by increasing the nucleation factor. On this basis, the catalytic mechanism of CoFe-PBA on the thermal decomposition of AP was discussed, and the possible interaction process between AP and CoFe-PBA during heating was proposed. At the same time, another interesting functional behavior to prevent AP from caking was discussed.

Image-free active autofocusing with dual modulation and its application to Fourier single-pixel imaging.

Autofocusing is widely used in applications where sharp image acquisition or projection is needed. Here we report an active autofocusing method for sharp image projection. The method works with wide-field structured illumination and single-pixel detection. To find the focus position, the method illuminates the target object with a set of 3-step phase-shifting Fourier basis patterns repeatedly and collects the backscattered light by using a single-pixel detector through a grating. Dual modulation-dynamic modulation by the time-varying structured illumination and static modulation by the grating-embeds the depth information for the target object in the resulting single-pixel measurements. As such, the focus position can be determined by recovering the Fourier coefficients from the single-pixel measurements and searching for the coefficient with the maximum magnitude. High-speed spatial light modulation not only enables rapid autofocusing but also makes the method work even when the lens system is in continuous motion or the focal length of the lens is continuously adjusted. We experimentally validate the reported method in a self-built digital projector and demonstrate the application of the method in Fourier single-pixel imaging.

Role of antiangiogenic agents in first-line treatment for advanced NSCLC in the era of immunotherapy.

BACKGROUND & OBJECTIVE: "Anti-angiogenetic drugs plus chemotherapy" (anti-angio-chemo) and "immune checkpoint inhibitors plus chemotherapy" (ICI-chemo) are superior to traditional chemotherapy in the first-line treatment of patients with advanced non-small-cell lung cancer (NSCLC). However, in the absence of a direct comparison of ICI-chemo with anti-angio-chemo, the superior one between them has not been decided, and the benefit of adding anti-angiogenetic agents to ICI-chemo remains controversial. This study aimed to investigate the role of antiangiogenic agents for advanced NSCLC in the era of immunotherapy. METHODS: Eligible randomized controlled trials (RCTs) comparing chemotherapy versus therapeutic regimens involving ICIs or anti-angiogenetic drugs were included. Outcomes included progression-free survival (PFS), overall survival (OS), objective response rate (ORR), and rate of grade 3-4 toxicity assessment. R-4.3.1 was utilized to perform the analysis. RESULTS: A total of 54 studies with a sample size of 25,046 were finally enrolled. "Atezolizumab + Bevacizumab + Chemotherapy" significantly improved the ORR compared with "Atezolizumab + Chemotherapy" (Odds ratio (OR) = 2.73, 95% confidence interval (CI): 1.27-5.87). The trend also favored "Atezolizumab + Bevacizumab + Chemotherapy" in PFS and OS (hazard ratio (HR) = 0.71, 95% CI: 0.39-1.31; HR = 0.94, 95% CI: 0.77-1.16, respectively). In addition, "Pembrolizumab + Chemotherapy" and "Camrelizumab + Chemotherapy" significantly prolonged the PFS compared to "Bevacizumab + Chemotherapy" (HR = 0.65, 95% CI: 0.46-0.92; HR = 0.63, 95% CI: 0.41-0.97; respectively). Meanwhile, "Pembrolizumab + Chemotherapy" and "Sintilimab + Chemotherapy" yielded more OS benefits than "Bevacizumab + Chemotherapy" (HR = 0.69, 95% CI: 0.56-0.83; HR = 0.64, 95%CI: 0.46-0.91; respectively). Scheme between "Atezolizumab + Bevacizumab + Chemotherapy" and "Atezolizumab + Chemotherapy" made no significant difference (OR = 1.18, 95%CI: 0.56-2.42) concerning the rate of grade 3-4 toxicity. It seemed that ICI-chemo yielded more improvement in quality-adjusted life-year (QALY) than "Bevacizumab + Chemotherapy" in cost-effectiveness analysis. CONCLUSION: Our results suggest that ICI-chemo is associated with potentially longer survival, better cost-effectiveness outcomes, and comparable safety profiles than anti-angio-chemo. Also, adding bevacizumab to ICI-chemo seemed to provide additional therapeutic benefits without adding treatment burden. Our findings would supplement the current standard of care and help the design of future clinical trials for the first-line treatment of patients with advanced NSCLC.

Molecular subtyping based on immune cell marker genes predicts prognosis and therapeutic response in patients with lung adenocarcinoma.

OBJECTIVE: Lung adenocarcinoma (LA) is one of the most common malignancies and is responsible for the greatest number of tumor-related deaths. Our research aimed to explore the molecular subtype signatures of LA to clarify the correlation among the immune microenvironment, clinical outcomes, and therapeutic response. METHODS: The LA immune cell marker genes (LICMGs) identified by single-cell RNA sequencing (scRNA-seq) analysis were used to discriminate the molecular subtypes and homologous immune and metabolic traits of GSE72094 LA cases. In addition, the model-building genes were identified from 1441 LICMGs by Cox-regression analysis, and a LA immune difference score (LIDscore) was developed to quantify individual differences in each patient, thereby predicting prognosis and susceptibility to immunotherapy and chemotherapy of LA patients. RESULTS: Patients of the GSE72094 cohort were divided into two distinct molecular subtypes based on LICMGs: immune activating subtype (Cluster-C1) and metabolically activating subtype (cluster-C2). The two molecular subtypes have distinct characteristics regarding prognosis, clinicopathology, genomics, immune microenvironment, and response to immunotherapy. Among the LICMGs, LGR4, GOLM1, CYP24A1, SFTPB, COL1A1, HLA-DQA1, MS4A7, PPARG, and IL7R were enrolled to construct a LIDscore model. Low-LIDscore patients had a higher survival rate due to abundant immune cell infiltration, activated immunity, and lower genetic variation, but probably the higher levels of Treg cells in the immune microenvironment lead to immune cell dysfunction and promote tumor immune escape, thus decreasing the responsiveness to immunotherapy compared with that of the high-LIDscore patients. Overall, high-LIDscore patients had a higher responsiveness to immunotherapy and a higher sensitivity to chemotherapy than the low-LIDscore group. CONCLUSIONS: Molecular subtypes based on LICMGs provided a promising strategy for predicting patient prognosis, biological characteristics, and immune microenvironment features. In addition, they helped identify the patients most likely to benefit from immunotherapy and chemotherapy.

Matricellular Protein Cilp1 Promotes Myocardial Fibrosis in Response to Myocardial Infarction.

[Figure: see text].

Pretreatment Serum Lactate Dehydrogenase and Metastases Numbers as Potential Determinants of Anti-PD-1 Therapy Outcome in Nasopharyngeal Carcinoma.

BACKGROUND: We aimed to investigate the determinant factors of anti-PD-1 therapy outcome in nasopharyngeal carcinoma (NPC). METHODS: In this retrospective study, we included 64 patients with recurrent/metastatic NPC. The association of patients' characteristics, C-reactive protein (CRP), neutrophil to lymphocyte ratio (NLR), and lactate dehydrogenase (LDH) with survival benefit of anti-PD-1 therapy were analyzed using Cox regression models and Kaplan-Meier analyses. Patients were divided based on the median value of CRP, NLR or LDH into different subgroups. RESULTS: At a median follow-up time of 11.4 months (range: 1-28 months), median progression-free survival (PFS) and overall survival (OS) were 1.9 months (95% CI, .18-3.6) and 15 months (95% CI, 10.9-19.1) months, respectively. Pretreatment metastases numbers was significant predictor of PFS (HR = 1.99; 95% CI 1.10-3.63; P = .024) and OS (HR = 2.77; 95% CI 1.36-5.61; P = .005). Baseline LDH level was independent predictor of OS (HR = 7.01; 95% CI 3.09-15.88; P < .001). Patients with LDH level >435 U/L at the baseline had significantly shorter PFS and OS compared to patients with LDH level ≤435 U/L (median PFS: 1.7 vs 3.5 months, P = .040; median OS: 3.7 vs 18.5 months, P < .001). Patients with non-durable clinical benefit (NDB) had significantly higher LDH level at the baseline compared to patients who achieved durable clinical benefit (DCB) (P = .025). Post-treatment levels of CRP, LDH, and NLR were decreased compared to baseline in patients with DCB (P = .030, P = .088, and P = .066, respectively), whereas, there was a significant increase in post-treatment level of LDH compared with baseline in patients with NDB (P = .024). CONCLUSIONS: LDH level at the baseline was an independent predictor of OS and pretreatment metastases numbers was a significant predictor of PFS and OS.

A diagnostic approach integrated multimodal radiomics with machine learning models based on lumbar spine CT and X-ray for osteoporosis.

INTRODUCTION: The aim of this analysis is to construct a combined model that integrates radiomics, clinical risk factors, and machine learning algorithms to diagnose osteoporosis in patients and explore its potential in clinical applications. MATERIALS AND METHODS: A retrospective analysis was conducted on 616 lumbar spine. Radiomics features were extracted from the computed tomography (CT) scans and anteroposterior and lateral X-ray images of the lumbar spine. Logistic regression (LR), support vector machine (SVM), and random forest (RF) algorithms were used to construct radiomics models. The receiver operating characteristic curve (ROC) was employed to select the best-performing model. Clinical risk factors were identified through univariate logistic regression analysis (ULRA) and multivariate logistic regression analysis (MLRA) and utilized to develop a clinical model. A combined model was then created by merging radiomics and clinical risk factors. The performance of the models was evaluated using ROC curve analysis, and the clinical value of the models was assessed using decision curve analysis (DCA). RESULTS: A total of 4858 radiomics features were extracted. Among the radiomics models, the SVM model demonstrated the optimal diagnostic capabilities and accuracy, with an area under the curve (AUC) of 0.958 (0.9405-0.9762) in the training cohort and 0.907 (0.8648-0.9492) in the test cohort. Furthermore, the combined model exhibited an AUC of 0.959 (0.9412-0.9763) in the training cohort and 0.910 (0.8690-0.9506) in the test cohort. CONCLUSION: The combined model displayed outstanding ability in diagnosing osteoporosis, providing a safe and efficient method for clinical decision-making.

SurfPB: A GPU-Accelerated Electrostatic Calculation and Visualization Tool for Biomolecules.

In this work, we present SurfPB as a useful tool for the study of biomolecules. It can do many typical calculations, including the molecular surface, electrostatic potential, solvation free energy, entropy, and binding free energy. Among all of the calculations, the entropy calculation is the most time-consuming one. In SurfPB, the calculation can be performed in a vacuum or implicit solvent and accelerated on GPU. The Poisson-Boltzmann equation solver is accelerated on GPU as well. Moreover, we developed a graphical user interface for SurfPB. It allows users to input the parameters and complete the whole calculation in a visual way. The calculated electrostatic potentials are shown on the molecular surface in a three-dimensional scene.