Pharmacological suppression of the OTUD4/CD73 proteolytic axis revives antitumor immunity against immune-suppressive breast cancers.

Despite widespread utilization of immunotherapy, treating immune-cold tumors remains a challenge. Multiomic analyses and experimental validation identified the OTUD4/CD73 proteolytic axis as a promising target in treating immune-suppressive triple negative breast cancer (TNBC). Mechanistically, deubiquitylation of CD73 by OTUD4 counteracted its ubiquitylation by TRIM21, resulting in CD73 stabilization inhibiting tumor immune responses. We further demonstrated the importance of TGF-ß signaling for orchestrating the OTUD4/CD73 proteolytic axis within tumor cells. Spatial transcriptomics profiling discovered spatially resolved features of interacting malignant and immune cells pertaining to expression levels of OTUD4 and CD73. In addition, ST80, a newly developed inhibitor, specifically disrupted proteolytic interaction between CD73 and OTUD4, leading to reinvigoration of cytotoxic CD8+ T cell activities. In preclinical models of TNBC, ST80 treatment sensitized refractory tumors to anti-PD-L1 therapy. Collectively, our findings uncover what we believe to be a novel strategy for targeting the immunosuppressive OTUD4/CD73 proteolytic axis in treating immune-suppressive breast cancers with the inhibitor ST80.

Machine Learning Predicts Oxaliplatin Benefit in Early Colon Cancer.

PURPOSE: A combination of fluorouracil, leucovorin, and oxaliplatin (FOLFOX) is the standard for adjuvant therapy of resected early-stage colon cancer (CC). Oxaliplatin leads to lasting and disabling neurotoxicity. Reserving the regimen for patients who benefit from oxaliplatin would maximize efficacy and minimize unnecessary adverse side effects. METHODS: We trained a new machine learning model, referred to as the colon oxaliplatin signature (COLOXIS) model, for predicting response to oxaliplatin-containing regimens. We examined whether COLOXIS was predictive of oxaliplatin benefits in the CC adjuvant setting among 1,065 patients treated with 5-fluorouracil plus leucovorin (FULV; n = 421) or FULV + oxaliplatin (FOLFOX; n = 644) from NSABP C-07 and C-08 phase III trials. The COLOXIS model dichotomizes patients into COLOXIS+ (oxaliplatin responder) and COLOXIS- (nonresponder) groups. Eight-year recurrence-free survival was used to evaluate oxaliplatin benefits within each of the groups, and the predictive value of the COLOXIS model was assessed using the P value associated with the interaction term (int P) between the model prediction and the treatment effect. RESULTS: Among 1,065 patients, 526 were predicted as COLOXIS+ and 539 as COLOXIS-. The COLOXIS+ prediction was associated with prognosis for FULV-treated patients (hazard ratio [HR], 1.52 [95% CI, 1.07 to 2.15]; P = .017). The model was predictive of oxaliplatin benefits: COLOXIS+ patients benefited from oxaliplatin (HR, 0.65 [95% CI, 0.48 to 0.89]; P = .0065; int P = .03), but COLOXIS- patients did not (COLOXIS- HR, 1.08 [95% CI, 0.77 to 1.52]; P = .65). CONCLUSION: The COLOXIS model is predictive of oxaliplatin benefits in the CC adjuvant setting. The results provide evidence supporting a change in CC adjuvant therapy: reserve oxaliplatin only for COLOXIS+ patients, but further investigation is warranted.

Measuring the composition of the tumor microenvironment with transcriptome analysis: past, present and future.

Interactions between tumor cells and immune cells in the tumor microenvironment (TME) play a vital role the mechanisms of immune evasion, by which cancer cells escape immune elimination. Thus, the characterization and quantification of different components in the TME is a hot topic in molecular biology and drug discovery. Since the development of transcriptome sequencing in bulk tissue, single cells and spatial dimensions, there are increasing methods emerging to deconvolute and subtype the TME. This review discusses and compares such computational strategies and downstream subtyping analyses. Integrative analyses of the transcriptome with other data, such as epigenetics and T-cell receptor sequencing, are needed to obtain comprehensive knowledge of the dynamic TME.

Tea Polyphenols Inhibit the Occurrence of Enzymatic Browning in Fresh-Cut Potatoes by Regulating Phenylpropanoid and ROS Metabolism.

During fresh-cut processing, potatoes lose their inherent protective cellular structure, leading to enzymatic browning that compromises sensory and edible quality. Tea polyphenols (TPs), natural preservatives with potent reducing properties, are hypothesized to impact this browning process. However, their influence and regulatory mechanism on the enzymatic browning of fresh-cut potatoes remain poorly understood. This study used the "Holland Seven" potato as the research material to explore the effects of a treatment with different TP concentrations (0.1 g L-1, 0.2 g L-1, and 0.3 g L-1) on the browning phenomenon and quality of fresh-cut potatoes during storage. The results showed that appropriate concentrations of TP treatment had a good preservation effect on the appearance and edible quality of fresh-cut potatoes. Furthermore, exogenous TP treatment reduced the content of enzymatic browning substrates (caffeic acid, p-coumaric acid, and ferulic acid) by regulating phenylpropanoid metabolism. Meanwhile, TP treatment augmented the activities of antioxidative enzymes (superoxide dismutase, catalase, ascorbate peroxidase, and glutathione reductase), maintained higher levels of ascorbic acid (Vc), and reduced glutathione (GSH). Consequently, the TP treatment could inhibit enzymatic browning by regulating reactive oxygen species (ROS) metabolism and the Vc-GSH cycle in fresh-cut potatoes.

FAK loss reduces BRAFV600E-induced ERK phosphorylation to promote intestinal stemness and cecal tumor formation.

BRAF V600E mutation is a driver mutation in the serrated pathway to colorectal cancers. BRAFV600E drives tumorigenesis through constitutive downstream extracellular signal-regulated kinase (ERK) activation, but high-intensity ERK activation can also trigger tumor suppression. Whether and how oncogenic ERK signaling can be intrinsically adjusted to a "just-right" level optimal for tumorigenesis remains undetermined. In this study, we found that FAK (Focal adhesion kinase) expression was reduced in BRAFV600E-mutant adenomas/polyps in mice and patients. In Vill-Cre;BRAFV600E/+;Fakfl/fl mice, Fak deletion maximized BRAFV600E's oncogenic activity and increased cecal tumor incidence to 100%. Mechanistically, our results showed that Fak loss, without jeopardizing BRAFV600E-induced ERK pathway transcriptional output, reduced EGFR (epidermal growth factor receptor)-dependent ERK phosphorylation. Reduction in ERK phosphorylation increased the level of Lgr4, promoting intestinal stemness and cecal tumor formation. Our findings show that a "just-right" ERK signaling optimal for BRAFV600E-induced cecal tumor formation can be achieved via Fak loss-mediated downregulation of ERK phosphorylation.

[Comparison of posterolateral approach and combined approach in treatment of Mason type 2B posterior malleolar fracture].

Objective: To compare the effectiveness between the posterolateral approach and the posterolateral combined posteromedial approaches in the treatment of Mason type 2B posterior malleolar fracture. Methods: A retrospective analysis was performed on the clinical data of 79 patients with posterior ankle fracture who met the selection criteria between January 2015 and January 2022. There were 62 cases of Mason 2B Pilon subtype and 17 cases of avulsion subtype. Among Mason 2B Pilon subtype patients, 35 were treated with posterolateral approach (group A), 27 patients were treated with combined approach (group B). There was no significant difference in gender, age, injured side, cause of injury, time from injury to operation, preoperative hospital stay, preoperative visualanalogue scale (VAS) score, and intraoperative internal fixation between the two groups ( P>0.05). All patients with Mason 2B avulsion subtype were treated by posterolateral approach, including 7 males and 10 females, aged from 25 to 68 years, with an average of 46.1 years. The operation time, intraoperative blood loss, postoperative hospital stay, and complications were recorded. The reduction quality was evaluated by Ovadia deals radiographic score, and the ankle function and pain were evaluated by VAS score, American Orthopaedic Foot and Ankle Society (AOFAS) score, and ankle range of motion. Results: Mason 2B Pilon subtype: There was no significant difference in operation time, intraoperative blood loss, postoperative hospital stay, and follow-up time between the two groups ( P>0.05). The radiological evaluation of Ovadia deals in group A was significantly worse than that in group B ( P<0.05). The VAS score in the two groups significantly improved at each time point after operation, and the VAS score and AOFAS score further improved with the extension of time after operation, and the differences were significant ( P<0.05). Except that the AOFAS score of group A was significantly lower than that of group B at last follow-up ( P<0.05), there was no significant difference in VAS score and AOFAS score between the two groups at other time points ( P>0.05). At last follow-up, the ankle range of motion in group A was significantly less than that in group B ( P<0.05). There was no significant difference in the incidence of sural nerve injury, deep tissue infection, limitation of toe movement, and traumatic ankle arthritis between the two groups ( P>0.05). Mason 2B avulsion subtype: The operation time was (119.47±20.61) minutes and the intraoperative blood loss was 50 (35, 55) mL. Seventeen patients were followed up 13-25 months, with an average of 18 months. The Ovadia deals score was excellent in 10 cases, good in 6 cases, and poor in 1 case at 1 week after operation, and the excellent and good rate was 94.1%. All fractures healed in 8-18 weeks with an average of 12.35 weeks. There were 1 case of sural nerve injury and 3 cases of traumatic ankle arthritis after operation. No deep tissue infection or limitation of toe movement occurred. The VAS score decreased significantly and AOFAS score increased significantly with time, and the differences were significant between different time points before and after operation ( P<0.05). The ankle range of motion at last follow-up was (56.71±2.47)°. Conclusion: Compared with the posterolateral approach, the combined approach is a better choice for the treatment of Mason 2B Pilon subtype. If the posteromedial bone block does not affect the reduction of the medial malleolus, the posterolateral approach can achieve good effectiveness for Mason 2B avulsion subtype.

An individualized Bayesian method for estimating genomic variants of hypertension.

BACKGROUND: Genomic variants of the disease are often discovered nowadays through population-based genome-wide association studies (GWAS). Identifying genomic variations potentially underlying a phenotype, such as hypertension, in an individual is important for designing personalized treatment; however, population-level models, such as GWAS, may not capture all the important, individualized factors well. In addition, GWAS typically requires a large sample size to detect the association of low-frequency genomic variants with sufficient power. Here, we report an individualized Bayesian inference (IBI) algorithm for estimating the genomic variants that influence complex traits, such as hypertension, at the level of an individual (e.g., a patient). By modeling at the level of the individual, IBI seeks to find genomic variants observed in the individual's genome that provide a strong explanation of the phenotype observed in this individual. RESULTS: We applied the IBI algorithm to the data from the Framingham Heart Study to explore the genomic influences of hypertension. Among the top-ranking variants identified by IBI and GWAS, there is a significant number of shared variants (intersection); the unique variants identified only by IBI tend to have relatively lower minor allele frequency than those identified by GWAS. In addition, IBI discovered more individualized and diverse variants that explain hypertension patients better than GWAS. Furthermore, IBI found several well-known low-frequency variants as well as genes related to blood pressure that GWAS missed in the same cohort. Finally, IBI identified top-ranked variants that predicted hypertension better than GWAS, according to the area under the ROC curve. CONCLUSIONS: The results support IBI as a promising approach for complementing GWAS, especially in detecting low-frequency genomic variants as well as learning personalized genomic variants of clinical traits and disease, such as the complex trait of hypertension, to help advance precision medicine.

scGEM: Unveiling the Nested Tree-Structured Gene Co-Expressing Modules in Single Cell Transcriptome Data.

BACKGROUND: Single-cell transcriptome analysis has fundamentally changed biological research by allowing higher-resolution computational analysis of individual cells and subsets of cell types. However, few methods have met the need to recognize and quantify the underlying cellular programs that determine the specialization and differentiation of the cell types. METHODS: In this study, we present scGEM, a nested tree-structured nonparametric Bayesian model, to reveal the gene co-expression modules (GEMs) reflecting transcriptome processes in single cells. RESULTS: We show that scGEM can discover shared and specialized transcriptome signals across different cell types using peripheral blood mononuclear single cells and early brain development single cells. scGEM outperformed other methods in perplexity and topic coherence (p < 0.001) on our simulation data. Larger datasets, deeper trees and pre-trained models are shown to be positively associated with better scGEM performance. The GEMs obtained from triple-negative breast cancer single cells exhibited better correlations with lymphocyte infiltration (p = 0.009) and the cell cycle (p < 0.001) than other methods in additional validation on the bulk RNAseq dataset. CONCLUSIONS: Altogether, we demonstrate that scGEM can be used to model the hidden cellular functions of single cells, thereby unveiling the specialization and generalization of transcriptomic programs across different types of cells.

Predicting Long-Term Care Service Demands for Cancer Patients: A Machine Learning Approach.

BACKGROUND: Long-term care (LTC) service demands among cancer patients are significantly understudied, leading to gaps in healthcare resource allocation and policymaking. OBJECTIVE: This study aimed to predict LTC service demands for cancer patients and identify the crucial factors. METHODS: 3333 cases of cancers were included. We further developed two specialized prediction models: a Unified Prediction Model (UPM) and a Category-Specific Prediction Model (CSPM). The UPM offered generalized forecasts by treating all services as identical, while the CSPM built individual predictive models for each specific service type. Sensitivity analysis was also conducted to find optimal usage cutoff points for determining the usage and non-usage cases. RESULTS: Service usage differences in lung, liver, brain, and pancreatic cancers were significant. For the UPM, the top 20 performance model cutoff points were adopted, such as through Logistic Regression (LR), Quadratic Discriminant Analysis (QDA), and XGBoost (XGB), achieving an AUROC range of 0.707 to 0.728. The CSPM demonstrated performance with an AUROC ranging from 0.777 to 0.837 for the top five most frequently used services. The most critical predictive factors were the types of cancer, patients' age and female caregivers, and specific health needs. CONCLUSION: The results of our study provide valuable information for healthcare decisions, resource allocation optimization, and personalized long-term care usage for cancer patients.

Amphiregulin couples IL1RL1+ regulatory T cells and cancer-associated fibroblasts to impede antitumor immunity.

Regulatory T (Treg) cells and cancer-associated fibroblasts (CAFs) jointly promote tumor immune tolerance and tumorigenesis. The molecular apparatus that drives Treg cell and CAF coordination in the tumor microenvironment (TME) remains elusive. Interleukin 33 (IL-33) has been shown to enhance fibrosis and IL1RL1+ Treg cell accumulation during tumorigenesis and tissue repair. We demonstrated that IL1RL1 signaling in Treg cells greatly dampened the antitumor activity of both IL-33 and PD-1 blockade. Whole tumor single-cell RNA sequencing (scRNA-seq) analysis and blockade experiments revealed that the amphiregulin (AREG)-epidermal growth factor receptor (EGFR) axis mediated cross-talk between IL1RL1+ Treg cells and CAFs. We further demonstrated that the AREG/EGFR axis enables Treg cells to promote a profibrotic and immunosuppressive functional state of CAFs. Moreover, AREG mAbs and IL-33 concertedly inhibited tumor growth. Our study reveals a previously unidentified AREG/EGFR-mediated Treg/CAF coupling that controls the bifurcation of fibroblast functional states and is a critical barrier for cancer immunotherapy.

Revealing the Impact of Genomic Alterations on Cancer Cell Signaling with an Interpretable Deep Learning Model.

Cancer is a disease of aberrant cellular signaling resulting from somatic genomic alterations (SGAs). Heterogeneous SGA events in tumors lead to tumor-specific signaling system aberrations. We interpret the cancer signaling system as a causal graphical model, where SGAs affect signaling proteins, propagate their effects through signal transduction, and ultimately change gene expression. To represent such a system, we developed a deep learning model called redundant-input neural network (RINN) with a transparent redundant-input architecture. Our findings demonstrate that by utilizing SGAs as inputs, the RINN can encode their impact on the signaling system and predict gene expression accurately when measured as the area under ROC curves. Moreover, the RINN can discover the shared functional impact (similar embeddings) of SGAs that perturb a common signaling pathway (e.g., PI3K, Nrf2, and TGF). Furthermore, the RINN exhibits the ability to discover known relationships in cellular signaling systems.

An interpretable deep learning framework for genome-informed precision oncology.

Cancers result from aberrations in cellular signaling systems, typically resulting from driver somatic genome alterations (SGAs) in individual tumors. Precision oncology requires understanding the cellular state and selecting medications that induce vulnerability in cancer cells under such conditions. To this end, we developed a computational framework consisting of two components: 1) A representation-learning component, which learns a representation of the cellular signaling systems when perturbed by SGAs, using a biologically-motivated and interpretable deep learning model. 2) A drug-response-prediction component, which predicts the response to drugs by leveraging the information of the cellular state of the cancer cells derived by the first component. Our cell-state-oriented framework significantly enhances the accuracy of genome-informed prediction of drug responses in comparison to models that directly use SGAs as inputs. Importantly, our framework enables the prediction of response to chemotherapy agents based on SGAs, thus expanding genome-informed precision oncology beyond molecularly targeted drugs.

Identifying Early-Stage Changes in Volatile Organic Compounds of Ceratocystis fimbriata Ellis & Halsted-Infected Sweet Potatoes (Ipomoea batatas L. Lam) Using Headspace Gas Chromatography-Ion Mobility Spectrometry.

Ceratocystis fimbriata Ellis & Halsted is the pathogen causing black rot in sweet potatoes that can lead to flavor change and toxin release. This study detected the volatile organic compounds (VOCs) of C. fimbriata-infected sweet potatoes in the early stages using headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS). A total of 55 VOCs were identified, including aldehydes, alcohols, esters, ketones, and others. The content of aldehydes and ketones showed a decreasing trend, while alcohols and esters showed an increasing trend. An increase in infection time elevated the content of malondialdehyde (MDA) and pyruvate, while the starch content decreased, the content of soluble protein initially increased, then decreased, and the activities of lipoxygenase (LOX), pyruvate decarboxylase (PDC), alcohol dehydrogenase (ADH), and phenylalanine ammonia-lyase (PAL) increased. The changes in VOCs were closely related to the content of MDA, starch, pyruvate, and the activities of LOX, PDC, ADH, and PAL. Sweet potatoes showed a good discrimination effect by principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) from 0 to 72 h. Twenty-five differential VOCs could be used as early-stage characteristic compounds of C. fimbriata-infected sweet potatoes for early disease monitoring.

Accurate estimation of rare cell type fractions from tissue omics data via hierarchical deconvolution.

Bulk transcriptomics in tissue samples reflects the average expression levels across different cell types and is highly influenced by cellular fractions. As such, it is critical to estimate cellular fractions to both deconfound differential expression analyses and infer cell type-specific differential expression. Since experimentally counting cells is infeasible in most tissues and studies, in silico cellular deconvolution methods have been developed as an alternative. However, existing methods are designed for tissues consisting of clearly distinguishable cell types and have difficulties estimating highly correlated or rare cell types. To address this challenge, we propose Hierarchical Deconvolution (HiDecon) that uses single-cell RNA sequencing references and a hierarchical cell type tree, which models the similarities among cell types and cell differentiation relationships, to estimate cellular fractions in bulk data. By coordinating cell fractions across layers of the hierarchical tree, cellular fraction information is passed up and down the tree, which helps correct estimation biases by pooling information across related cell types. The flexible hierarchical tree structure also enables estimating rare cell fractions by splitting the tree to higher resolutions. Through simulations and real data applications with the ground truth of measured cellular fractions, we demonstrate that HiDecon significantly outperforms existing methods and accurately estimates cellular fractions.

Derivation of copper water quality criteria in Bohai Bay for the protection of local aquatic life and the ecological risk assessment.

Developing effective marine water quality criteria (WQC) is crucial for controlling marine contamination and protecting marine life. The WQC for copper is urgently needed due to the toxicity and widespread of copper contamination. In this work, both short-term water quality criteria (SWQC) and long-term water quality criteria (LWQC) under 10 % effect endpoints were derived by using the model averaging of species sensitivity distribution (SSD10) method for Bohai Bay. The WQC values were obtained directly from the hazardous concentration for 5 % of species (HC5) values, which removes the influence of arbitrary assessment factor (AF). Modifications to the acute-chronic ratio (ACR) strategies and the inclusion of the test toxicity data of local species also improved the accuracy and applicability of the WQC values. The derived SWQC and LWQC were 2.21 and 0.45 µg/L, respectively. Furthermore, the overall risk level of copper in Bohai Bay was evaluated by using the risk quotient (RQ) method, and the results showed it was at a moderate-low level. This study provides a new approach for the derivation of the WQC for Cu and the risk assessment of Bohai Bay, which is essential for the protection of local aquatic life and provides guidance to the establishment of the national WQC.

Geometrical and magnetic properties of small titanium and chromium clusters on monolayer hexagonal boron nitride.

Magnetic clusters on an insulating substrate are potential candidates for spin-based quantum devices. Here we investigate the geometric, electronic, and magnetic structures of small Ti and Cr clusters, from dimers to pentamers, adsorbed on a single-layer hexagonal boron nitride (h-BN) sheet within the framework of density functional theory. The stable adsorption configurations of the Ti clusters and Cr clusters composed of the same number of atoms are found to be totally different from each other. The difference in their bonding mechanisms has been revealed by the density of states and the charge density difference of the corresponding adsorption systems. While chemical bonds are formed between the Ti atoms and the supporting sheet, the Cr clusters are found in the physisorption state on the substrate. In addition, it is shown that the h-BN sheet is energetically favorable for building three-dimensional Ti clusters. These findings support the use of h-BN as a suitable decoupling substrate for manipulation of quantum spin states in small transition metal (TM) clusters and fabrication of devices based on them.

Proteolytic regulation of CD73 by TRIM21 orchestrates tumor immunogenicity.

Despite the rapid utilization of immunotherapy, emerging challenges to the current immune checkpoint blockade need to be resolved. Here, we report that elevation of CD73 levels due to its aberrant turnover is correlated with poor prognosis in immune-cold triple-negative breast cancers (TNBCs). We have identified TRIM21 as an E3 ligase that governs CD73 destruction. Disruption of TRIM21 stabilizes CD73 that in turn enhances CD73-catalyzed production of adenosine, resulting in the suppression of CD8+ T cell function. Replacement of lysine 133, 208, 262, and 321 residues by arginine on CD73 attenuated CD73 ubiquitylation and degradation. Diminishing of CD73 ubiquitylation remarkably promotes tumor growth and impedes antitumor immunity. In addition, a TRIM21high/CD73low signature in a subgroup of human breast malignancies was associated with a favorable immune profile. Collectively, our findings uncover a mechanism that governs CD73 proteolysis and point to a new therapeutic strategy by modulating CD73 ubiquitylation.

[Comparison of full thread compression cannulated screw and partial thread cannulated screw in treatment of femoral neck fracture].

Objective: To compare the effectiveness of full thread compression cannulated screw and partial thread cannulated screw in the treatment of femoral neck fracture. Methods: A retrospective analysis was made on 152 patients with femoral neck fractures, who met the selection criteria, between April 2013 and February 2021. The fractures were fixed with the full thread compression cannulated screws in 74 cases (trial group) and the partial thread cannulated screws in 78 cases (control group). There was no significant difference in general data such as age, gender, body mass index, cause of injury, time from injury to operation, and the side, Garden typing, Pauwels typing of fracture between the two groups (P>0.05). The operation time, intraoperative blood loss, hospital stay, follow-up time, and Harris score were recorded in both groups. X-ray films were performed to evaluate the quality of fracture reduction and bone healing, the changes of neck-shaft angle, the changes of femoral neck, as well as the occurrence of internal fixation failure, screw back-out, and osteonecrosis of the femoral head. Results: There was no significant difference in operation time and hospital stay between the two groups (P>0.05). However, the intraoperative blood loss in the trial group was significantly lower than that in the control group (P<0.05). Patients in both groups were followed up, with the follow-up time of (24.11±4.04) months in the trial group and (24.10±4.42) months in the control group, and the difference was not significant (P>0.05). Postoperative X-ray films showed that there was no significant difference in fracture reduction grading between the two groups (P>0.05). Six cases in the trial group developed bone nonunion and 7 cases in the control group, the fractures of the other patients healed, and the healing time was significantly shorter in the trial group than in the control group (P<0.05). There was no significant difference in the incidence of bone nonunion between the two groups (P>0.05). During follow-up, 2 cases in the trial group and 5 cases in the control group had osteonecrosis of the femoral head, the difference was not significant (P>0.05), and the patients with osteonecrosis of the femoral head were treated with secondary operation. The screw back-out occurred in 3 cases of the trial group and in 9 cases of the control group, showing no significant difference (P>0.05). But the screw back-out distance was significantly shorter in the trial group than in the control group (P<0.05). The incidence of internal fixation failure in the trial group (4 cases) was significantly lower than that in the control group (14 cases) (P<0.05). The incidence of femoral neck shortening and the change of neck-shaft angle at 1 year after operation were significantly lower in the trial group than in the control group (P<0.05). The Harris score at last follow-up was significantly higher in the trial group than in the control group (P<0.05). Conclusion: Compared with the partial threaded cannulated screws, the full threaded cannulated compression screws can effectively maintain fracture reduction, avoid femoral neck shortening, and internal fixation failure. It is a better choice for femoral neck fracture.

Advanced LD pumped 3.3 J/1 Hz nanosecond Nd:glass preamplifier for SG-II upgrade laser facility.

We demonstrate a laser-diode-pumped multipass Nd:glass laser amplifier with a range of advanced characteristics. The amplifier exhibits high extraction efficiency, enables arbitrary shaping of spatial beam intensity, and effectively suppresses frequency modulation to amplitude modulation conversion. Our approach achieves excellent beam quality via thermal lensing and thermal depolarization compensation. When a 1.82 mJ/5 ns laser pulse was injected into the amplifier, the output energy reached up to 3.3 J with a repetition rate of 1 Hz at a central wavelength of 1053.3 nm. The near-field modulation of the amplified output beam was below 1.2, and the far-field focusing ability of the beam was 90% at 2.9 times the diffraction limit. This laser amplifier system holds potential for integration as a preamplifier within the SG-II upgrade high power laser facility.

An individualized causal framework for learning intercellular communication networks that define microenvironments of individual tumors.

Cells within a tumor microenvironment (TME) dynamically communicate and influence each other's cellular states through an intercellular communication network (ICN). In cancers, intercellular communications underlie immune evasion mechanisms of individual tumors. We developed an individualized causal analysis framework for discovering tumor specific ICNs. Using head and neck squamous cell carcinoma (HNSCC) tumors as a testbed, we first mined single-cell RNA-sequencing data to discover gene expression modules (GEMs) that reflect the states of transcriptomic processes within tumor and stromal single cells. By deconvoluting bulk transcriptomes of HNSCC tumors profiled by The Cancer Genome Atlas (TCGA), we estimated the activation states of these transcriptomic processes in individual tumors. Finally, we applied individualized causal network learning to discover an ICN within each tumor. Our results show that cellular states of cells in TMEs are coordinated through ICNs that enable multi-way communications among epithelial, fibroblast, endothelial, and immune cells. Further analyses of individual ICNs revealed structural patterns that were shared across subsets of tumors, leading to the discovery of 4 different subtypes of networks that underlie disparate TMEs of HNSCC. Patients with distinct TMEs exhibited significantly different clinical outcomes. Our results show that the capability of estimating individual ICNs reveals heterogeneity of ICNs and sheds light on the importance of intercellular communication in impacting disease development and progression.