Aggressive vertebral hemangiomas contain no adipose tissue resulting in thoracic spine kyphosis: A case report

RATIONALE

Aggressive vertebral hemangiomas (AVHs) destroy continuous vertebral bodies and intervertebral discs and resulting in spinal kyphosis is extremely rare. The very aggressive behavior was attributable to its significant vascular component and contained no adipose tissue.

PATIENT CONCERNS

We report a case of thoracic spine kyphosis of AVHs with multiple vertebral bodies and intervertebral disc destruction in a 45-year-old woman.

DIAGNOSES

Based on the imaging studies, the patient underwent surgical removal of this lesion and spinal reconstruction. Histopathology consistent with vertebral hemangioma and contained no adipose.

INTERVENTIONS

The patient underwent surgical removal of the lesion and spinal reconstruction. After subperiosteal dissection of the paraspinal muscles and exposure of the laminae, the laminae of the T5-7 vertebrae were removed and exposing the lesion. The lesion was soft and showed cystic changes, completely curetted and autogenous bone was implanted. Vertebroplasty was performed through T3-T9 pedicles bilaterally. Pedicle screw fixation was performed for segmental fixation and fusion.

OUTCOMES

After 9 days of operation, the incision healed cleanly and free of pain. She was discharged in good general condition. The patient remained asymptomatic after follow-up 6 months of postoperative.

LESSONS

AVHs destroy multiple vertebral bodies and intervertebral discs and resulting in spinal kyphosis is extremely rare.

Rapid establishment of municipal sewage partial denitrification-anammox for nitrogen removal through inoculation with side-stream anammox biofilm without domestication

Mainstream partial denitrification anammox was achieved through inoculation of side-stream mature partial nitritation anammox biofilm without domestication. The contribution of anammox to nitrogen removal was 29.4 %. Moreover, prolonging anoxic hydraulic retention time and introducing side-stream nitrite under different carbon/nitrogen ratios enriched anammox bacteria. The abundance of anammox bacteria increased by ∼ 10 times ((2.19 ± 0.17) × 1012 copies gene / g dry sludge) with a total relative abundance of 18.51 %. During 258 days of operation, the contribution of anammox to nitrogen removal gradually increased to 68.8 %. The total nitrogen in the effluent decreased to 8.84 mg/L with a total nitrogen removal efficiency of 76.4 % under a carbon/nitrogen ratio of 3. This paper proposes a novel way to rapidly achieve mainstream partial denitrification anammox via inoculation with side-stream mature partial nitritation anammox biofilm. This method achieves advanced nitrogen removal from municipal wastewater, even under low carbon/nitrogen ratios.

Sildenafil improves hemodynamic changes caused by acute pulmonary embolism by inhibiting Rho kinase activity

OBJECTIVE

This study examined the effects of sildenafil on acute pulmonary embolism (APE) using a rat model.

METHODS

Sprague-Dawley rats were randomly divided into the sham, pulmonary thromboembolism (PTE), and sildenafil groups. The sham and PTE groups received normal saline once daily via gavage for 14 consecutive days, whereas the sildenafil group received sildenafil (0.5 mg/kg/day) once daily via gavage for 14 consecutive days. Autologous emboli were prepared from blood samples collected from the left femoral artery of rats in each group on day 13, and autologous emboli were injected into the jugular vein cannula of rats in the PTE and sildenafil groups on day 14. Sham-treated rats received the same volume of saline. Right systolic ventricular pressure (RVSP) and mean pulmonary arterial pressure (MPAP) were used to assess pulmonary embolism, and western blotting and enzyme-linked immunosorbent assay were used to detect relevant markers.

RESULTS

The Rho kinase signaling pathway was significantly activated in rats with APE, and sildenafil significantly inhibited this activation.

CONCLUSIONS

Sildenafil protected against APE through inhibiting Rho kinase activity, thereby reducing pulmonary vasoconstriction and decreasing elevated pulmonary arterial pressure. These findings might provide new ideas for the clinical treatment of acute pulmonary thromboembolism.

Altered orientation dispersion index of white matter in individuals with insomnia during the COVID-19 pandemic: A study combining neuroimaging technique and Mendelian randomization

STUDY OBJECTIVES

Coronavirus disease 2019 (COVID-19) can lead to insomnia. However, associations between COVID-19-caused insomnia and white matter (WM) changes are unclear.

METHODS

All subjects had ever been infected with COVID-19. We investigated 89 insomniacs (29 chronic insomniacs, 33 new-onset insomniacs, 27 aggravated insomniacs) and 44 matched non-insomnia participants. Neurite orientation dispersion and density imaging (NODDI) was performed to identify micro-structural alterations of WM, and twelve scales related to sleeping status, memory, attention, learning, emotional status, and executive functions were used. Then, correlations between insomnia/cognitive-behavioral functions and diffusion metrics were tested. To eliminate influence of pre-COVID-19 factors on insomnia, causal relationships between COVID-19 and WM changes were validated by Mendelian randomization (MR) analysis. The significant brain regions of COVID-19-caused insomnia were intersected results of tract-based spatial statistics (TBSS) and MR analyses.

RESULTS

Compared to non-insomnia group, insomnia group and its subgroups including post-COVID-19 aggravated or unchanged chronic insomnia group had higher orientation dispersion index (ODI) in extensive brain regions. The left superior longitudinal fasciculus (SLF), left posterior thalamic radiation (PTR), and left cingulate gyrus (CG) were specific brain regions in COVID-19-induced insomnia aggravation. After Bonferroni correction, partial correlation analyses within insomnia group showed that ODI in left SLF was positively correlated with Pittsburgh sleep quality index (PSQI), insomnia severity index (ISI), and self-rating anxiety scale (SAS) scores; ODI in the left PTR was positively correlated with PSQI and ISI scores.

CONCLUSIONS

This study is a continuation of our previous research, which provided potential biomarkers for COVID-19-induced insomnia.

Real and synthetic Punjabi speech datasets for automatic speech recognition

Automatic speech recognition (ASR) has been an active area of research. Training with large annotated datasets is the key to the development of robust ASR systems. However, most available datasets are focused on high-resource languages like English, leaving a significant gap for low-resource languages. Among these languages is Punjabi, despite its large number of speakers, Punjabi lacks high-quality annotated datasets for accurate speech recognition. To address this gap, we introduce three labeled Punjabi speech datasets: Punjabi Speech (real speech dataset) and Google-synth/CMU-synth (synthesized speech datasets). The Punjabi Speech dataset consists of read speech recordings captured in various environments, including both studio and open settings. In addition, the Google-synth dataset is synthesized using Google's Punjabi text-to-speech cloud services. Furthermore, the CMU-synth dataset is created using the Clustergen model available in the Festival speech synthesis system developed by CMU. These datasets aim to facilitate the development of accurate Punjabi speech recognition systems, bridging the resource gap for this important language.

Preparation of Ceramic Fiber Threads with Enhanced Abrasion Resistance Performance

Ceramic fiber thread is one of the key components in flexible external thermal insulation blankets, and it has been applied in various fields as a flexible ceramic fibrous material with excellent deformability and high-temperature resistance. However, ceramic fiber threads are often subjected to reciprocating friction motion at specific bending angles, making them highly susceptible to abrade and fracture. Enhancing the abrasion resistance performance of ceramic fiber threads under bending conditions is the future trend and remains a significant challenge. Hence, we design and construct a novel polyurethane-modified coating on the ceramic fiber threads to improve their abrasion resistance performance. The effects of the types and concentrations of modifiers on the microstructure, abrasion resistance property, and tensile property of ceramic fiber threads are systematically investigated. The ceramic fiber threads, after modification with hexamethylene diisocyanate waterborne polyurethane (HDI-WPU) with a concentration of 3%, exhibit excellent abrasion resistance properties. The number of friction cycles at fracture of the modified ceramic fiber thread is more than three times, and the tensile strength is more than one and a half times, that of the original ceramic fiber thread, demonstrating the great potential of the HDI-WPU modifier for enhancing the abrasion resistance performance of ceramic fiber threads.

Preoperative CT-based deep learning radiomics model to predict lymph node metastasis and patient prognosis in bladder cancer: a two-center study

OBJECTIVE

To establish a model for predicting lymph node metastasis in bladder cancer (BCa) patients.

METHODS

We retroactively enrolled 239 patients who underwent three-phase CT and resection for BCa in two centers (training set, n = 185; external test set, n = 54). We reviewed the clinical characteristics and CT features to identify significant predictors to construct a clinical model. We extracted the hand-crafted radiomics features and deep learning features of the lesions. We used the Minimum Redundancy Maximum Relevance algorithm and the least absolute shrinkage and selection operator logistic regression algorithm to screen features. We used nine classifiers to establish the radiomics machine learning signatures. To compensate for the uneven distribution of the data, we used the synthetic minority over-sampling technique to retrain each machine-learning classifier. We constructed the combined model using the top-performing radiomics signature and clinical model, and finally presented as a nomogram. We evaluated the combined model's performance using the area under the receiver operating characteristic, accuracy, calibration curves, and decision curve analysis. We used the Kaplan-Meier survival curve to analyze the prognosis of BCa patients.

RESULTS

The combined model incorporating radiomics signature and clinical model achieved an area under the receiver operating characteristic of 0.834 (95% CI: 0.659-1.000) for the external test set. The calibration curves and decision curve analysis demonstrated exceptional calibration and promising clinical use. The combined model showed good risk stratification performance for progression-free survival.

CONCLUSION

The proposed CT-based combined model is effective and reliable for predicting lymph node status of BCa patients preoperatively.

CRITICAL RELEVANCE STATEMENT

Bladder cancer is a type of urogenital cancer that has a high morbidity and mortality rate. Lymph node metastasis is an independent risk factor for death in bladder cancer patients. This study aimed to investigate the performance of a deep learning radiomics model for preoperatively predicting lymph node metastasis in bladder cancer patients.

KEY POINTS

• Conventional imaging is not sufficiently accurate to determine lymph node status. • Deep learning radiomics model accurately predicted bladder cancer lymph node metastasis. • The proposed method showed satisfactory patient risk stratification for progression-free survival.

Ultrahigh Degree of Cationic Disorder, Configurational Entropy in New Type of High-Entropy Pseudobrookite Phase

High-entropy ceramics exhibit various excellent properties owing to their high configurational entropy, which is caused by multi-principal elements sharing one lattice site. The configurational entropy will further increase significantly if multi-principal elements randomly share two different lattice sites. For this purpose, pseudobrookite phase containing two cationic lattice sites (A and B sites) is selected, and corresponding high-entropy pseudobrookite (M2+ 0.4 M3+ 1.2 )Ti1.4 O5 is synthesized. Herein, the distribution of the 2-valent and 3-valent cations in the A and B sites are analysed in depth. The distance between the A and B sites in the crystal structure models which are constructed by the Rietveld analysis is calculated and defined as distance d. Meanwhile, the atomic column positions in the STEM images are quantified by a model-based mathematical algorithm, and the corresponding distance d are calculated. By comparing the distance d, it is determine that the 2-valent and 3-valent cations are jointly and disorderly distributed in the A and B sites in high-entropy (M2+ 0.4 M3+ 1.2 )Ti1.4 O5 . The density functional theory (DFT) simulations also demonstrate that this type of crystal structure is more thermodynamically stable. The higher degree of cationic disorder leads to a higher configurational entropy in high-entropy (M2+ 0.4 M3+ 1.2 )Ti1.4 O5 , and endows high-entropy (M2+ 0.4 M3+ 1.2 )Ti1.4 O5 with very low thermal conductivity (1.187-1.249 W m-1  K-1 ).

Flexo-/Piezoelectric Polarization Boosting Exciton Dissociation in Curved Two-Dimensional Carbon Nitride Photocatalyst

Two-dimensional (2D) carbon nitride (CN) materials have received tremendous attention as photocatalysts for clean energy and environmental treatment. However, the photocatalytic efficiency of CN is constrained by the high exciton binding energy and sluggish charge kinetics due to weak dielectric screening, impeding the overall process. Herein, localized flexo-/piezoelectric polarization is introduced via strain engineering, boosting exciton dissociation and promoting charge separation to enhance the multielectron photocatalytic process. Consequently, the exciton binding energy of polarized CN is reduced from 52 to 34 meV, and the hydrogen evolution yield increased by 2.9 times compared to that of the pristine CN. For other photocatalytic reactions (e.g., H2O2 production), the polarized CN also maintained a 2.1-fold increase compared to the pristine CN. This strategy of inducing localized polarization via strain engineering provides new insights for boosting photocatalytic reactions involving electrons.

Robust and high-efficient nitrogen removal from real sewage and waste activated sludge (WAS) reduction in zero-external carbon PN/A combined with in-situ fermentation-denitrification process under decreased temperatures

Despite the advantages of the combined anammox and fermentation-driven denitrification process in nitrogen removal and energy consumption, stable performance at decreased temperatures remains a challenge. In this study, a robust and high-efficient nitrogen removal efficiency (95.0-93.1 ∼ 86.8-93.4%) with desirable effluent quality (3.0-4.1 ∼ 7.9-4.9 mg/L) under long-term decreased temperatures (30 °C→25 °C→20 °C) was achieved in a zero-external carbon Partial Nitritation/Anammox combined with in-situ sludge Fermentation-Denitrification process treating sewage. Excellent sludge reduction averaged at 14.9% assuming no microbial growth. Increased hzsB mRNA (2.2-fold) and reduced Ea (80.9 kJ/mol) proved resilient anammox to lower temperature. RT-qPCR tests revealed increased NarG/NirK (5.1) and NarG/NirS (4.9) mRNA at 20 °C, suggesting higher NO3-→NO2- over NO2-→N2 pathway. Metagenomics unraveled dominant anammox bacteria (Candidatus_Brocadia, 2.27%), increased denitritation bacteria containing more NarG (Hyphomicrobium, 0.8%), fatty acid biosynthesis and CAZymes genes. Enhanced denitritation with recovered organics from sludge reserved nitrite for anammox and facilitated higher anammox contribution to N removal at 20 °C (42.4%) than 30 °C (39.5%). This study proposed an innovative low-temperature strategy for in-situ sludge fermentation, and demonstrated stability of advanced municipal wastewater treatment and sludge disposal through energy savings and carbon recovery under decreased temperatures.

Preoperative contrast-enhanced CT-based radiomics nomogram for differentiating benign and malignant primary retroperitoneal tumors

OBJECTIVES

This study evaluated the ability of a preoperative contrast-enhanced CT (CECT)-based radiomics nomogram to differentiate benign and malignant primary retroperitoneal tumors (PRT).

METHODS

Images and data from 340 patients with pathologically confirmed PRT were randomly placed into training (n = 239) and validation sets (n = 101). Two radiologists independently analyzed all CT images and made measurements. Key characteristics were identified through least absolute shrinkage selection combined with four machine-learning classifiers (support vector machine, generalized linear model, random forest, and artificial neural network back propagation) to create a radiomics signature. Demographic data and CECT characteristics were analyzed to formulate a clinico-radiological model. Independent clinical variables were merged with the best-performing radiomics signature to develop a radiomics nomogram. The discrimination capacity and clinical value of three models were quantified by the area under the receiver operating characteristics (AUC), accuracy, and decision curve analysis.

RESULTS

The radiomics nomogram was able to consistently differentiate between benign and malignant PRT in the training and validation datasets, with AUCs of 0.923 and 0.907, respectively. Decision curve analysis manifested that the nomogram achieved higher clinical net benefits than did separate use of the radiomics signature and clinico-radiological model.

CONCLUSIONS

The preoperative nomogram is valuable for differentiating between benign and malignant PRT; it can also aid in treatment planning.

KEY POINTS

• A noninvasive and accurate preoperative determination of benign and malignant PRT is crucial to identifying suitable treatments and predicting disease prognosis. • Associating the radiomics signature with clinical factors facilitates differentiation of malignant from benign PRT with improved diagnostic efficacy (AUC) and accuracy from 0.772 to 0.907 and from 0.723 to 0.842, respectively, compared with the clinico-radiological model alone. • For some PRT with anatomically special locations and when biopsy is extremely difficult and risky, a radiomics nomogram may provide a promising preoperative alternative for distinguishing benignity and malignancy.

CT-based deep learning radiomics nomogram for the prediction of pathological grade in bladder cancer: a multicenter study

BACKGROUND

To construct and assess a computed tomography (CT)-based deep learning radiomics nomogram (DLRN) for predicting the pathological grade of bladder cancer (BCa) preoperatively.

METHODS

We retrospectively enrolled 688 patients with BCa (469 in the training cohort, 219 in the external test cohort) who underwent surgical resection. We extracted handcrafted radiomics (HCR) features and deep learning (DL) features from three-phase CT images (including corticomedullary-phase [C-phase], nephrographic-phase [N-phase] and excretory-phase [E-phase]). We constructed predictive models using 11 machine learning classifiers, and we developed a DLRN by combining the radiomic signature with clinical factors. We assessed performance and clinical utility of the models with reference to the area under the curve (AUC), calibration curve, and decision curve analysis (DCA).

RESULTS

The support vector machine (SVM) classifier model based on HCR and DL combined features was the best radiomic signature, with AUC values of 0.953 and 0.943 in the training cohort and the external test cohort, respectively. The AUC values of the clinical model in the training cohort and the external test cohort were 0.752 and 0.745, respectively. DLRN performed well on both data cohorts (training cohort: AUC = 0.961; external test cohort: AUC = 0.947), and outperformed the clinical model and the optimal radiomic signature.

CONCLUSION

The proposed CT-based DLRN showed good diagnostic capability in distinguishing between high and low grade BCa.

Preoperative contrast-enhanced CT-based radiomics signature for predicting hypoxia-inducible factor 1α expression in retroperitoneal sarcoma

AIM

To develop and test a contrast-enhanced computed tomography (CECT)-based radiomics signature (RS) to preoperatively predict hypoxia-inducible factor 1α (HIF-1α) expression in retroperitoneal sarcoma (RPS).

MATERIALS AND METHODS

This study included 129 patients with RPS retrospectively who underwent CECT, including 64 male and 65 female patients (55 [2-84] years). Participants were divided into a training set comprising 85 patients and a test set comprising 44 patients. Clinical data and CECT findings of all patients were collected. RS construction was performed by the minimum redundancy maximum relevance method and least absolute shrinkage and selection operator algorithm. The clinical information was analysed by univariate and multivariate logistic regression analysis. The RS and risk factors were included to build a radiomics nomogram. The predictive efficacy of different models was evaluated by accuracy, area under the receiver operating characteristic curve (AUC), and decision curve analysis.

RESULTS

The RS combined signature was constructed on the basis of multi-phase CECT and had an accuracy of 0.795 and an AUC of 0.719 (95% confidence interval [CI], 0.552-0.886) in the test set, which were higher than that of the radiomics nomogram (accuracy: 0.636; AUC: 0.702 [95% CI, 0.547-0.857]) and the clinical model (accuracy: 0.682; AUC: 0.486 [95% CI, 0.324-0.647]). The decision curve analysis showed that the RS combined signature provided better clinical application than the clinical model and radiomics nomogram.

CONCLUSIONS

The multi-phase CECT-based RS constructed can be used as a powerful tool for predicting HIF-1α expression in patients with RPS.

Facilitating two-electron oxygen reduction with pyrrolic nitrogen sites for electrochemical hydrogen peroxide production

Electrocatalytic hydrogen peroxide (H₂O₂) production via the two-electron oxygen reduction reaction is a promising alternative to the energy-intensive and high-pollution anthraquinone oxidation process. However, developing advanced electrocatalysts with high H₂O₂ yield, selectivity, and durability is still challenging, because of the limited quantity and easy passivation of active sites on typical metal-containing catalysts, especially for the state-of-the-art single-atom ones. To address this, we report a graphene/mesoporous carbon composite for high-rate and high-efficiency 2e^- oxygen reduction catalysis. The coordination of pyrrolic-N sites -modulates the adsorption configuration of the *OOH species to provide a kinetically favorable pathway for H₂O₂ production. Consequently, the H₂O₂ yield approaches 30 mol g^-1 h^-1 with a Faradaic efficiency of 80% and excellent durability, yielding a high H₂O₂ concentration of 7.2 g L^-1. This strategy of manipulating the adsorption configuration of reactants with multiple non-metal active sites provides a strategy to design efficient and durable metal-free electrocatalyst for 2e^- oxygen reduction.

A Survey of Visual Transformers

Transformer, an attention-based encoder-decoder model, has already revolutionized the field of natural language processing (NLP). Inspired by such significant achievements, some pioneering works have recently been done on employing Transformer-liked architectures in the computer vision (CV) field, which have demonstrated their effectiveness on three fundamental CV tasks (classification, detection, and segmentation) as well as multiple sensory data stream (images, point clouds, and vision-language data). Because of their competitive modeling capabilities, the visual Transformers have achieved impressive performance improvements over multiple benchmarks as compared with modern convolution neural networks (CNNs). In this survey, we have reviewed over 100 of different visual Transformers comprehensively according to three fundamental CV tasks and different data stream types, where taxonomy is proposed to organize the representative methods according to their motivations, structures, and application scenarios. Because of their differences on training settings and dedicated vision tasks, we have also evaluated and compared all these existing visual Transformers under different configurations. Furthermore, we have revealed a series of essential but unexploited aspects that may empower such visual Transformers to stand out from numerous architectures, e.g., slack high-level semantic embeddings to bridge the gap between the visual Transformers and the sequential ones. Finally, two promising research directions are suggested for future investment. We will continue to update the latest articles and their released source codes at.

Cuttlefish-Bone-Structure-like Lamellar Porous Fiber-Based Ceramics with Enhanced Mechanical Performances

Porous fiber-based ceramics have been widely applied in various fields because of their excellent thermal insulation property and high thermal stability property. However, designing porous fibrous ceramics with enhanced comprehensive performances, such as low density, low thermal conductivity, and high mechanical properties at both room temperature and high temperature, is still a challenge and the future development trend. Hence, based on the lightweight cuttlefish bone that possesses a "wall-septa" structure with excellent mechanical performance, we design and fabricate a novel porous fibrous ceramic with the unique fiber-based dual structure of lamellas by the directional freeze-casting method and systematically investigate the effects of lamellar components on the microstructure and mechanical performances of the product. For the desired cuttlefish-bone-structure-like lamellar porous fiber-based ceramics (CLPFCs), the porous framework formed by the overlapping of transversely arranged fibers helps to reduce the density and thermal conductivity of the product, and the longitudinally arranged lamellar structure replaces traditional binders and plays an important role in improving the mechanical properties in the direction parallel to the X-Z plane. Compared with traditional porous fibrous materials reported in the literature, the CLPFCs with an Al₂O₃/SiO₂ molar ratio of 1:2 in the lamellar component exhibits prominent comprehensive performances, such as low density, excellent thermal insulation property, and outstanding mechanical performances at both room temperature and high temperature (3.46 MPa at 1300 °C), indicating that the CLPFCs are a promising candidate for applications in high-temperature thermal insulation systems.

Legacy and emerging poly- and perfluoroalkyl substances in wastewater treatment plant and receiving water: abundance, removal, and potential ecological risk

Poly- and perfluoroalkyl substances (PFASs) are toxic persistent organic pollutants and bioaccumulative chemicals, which affect the environment and ecology. PFASs in the wastewater treatment plant (WWTP) and receiving river downstream were investigated. Fourteen out of eighteen PFASs were detected, ranging from 197 to 0.14 ng L^-1. The main pollutants were 2,3,3,3-tetrafluoro-2-(1,1,2,2,3,3,3-heptafluoro-propoxy) propanoic acid (HFPO-DA), perfluorooctane sulfonate (PFOS), and perfluorooctanoic acid (PFOA). The concentration of HFPO-DA (181 ng L^-1) was the highest in influent, which indicated the use and emission of PFASs in the sewage collection region of WWTP changed from legacy to emerging ones. However, PFOS from catering wastewater as the main source was dominant PFASs in the reclaimed water. Biological treatment could be effective in the removal of PFASs, especially for HFPO-DA. HFPO-DA could directly bind to cytochrome P450 and bring potential ecotoxicity to the surrounding environment, and the ecological risk of degradation products should be under consideration. Coagulation might result in PFASs release from sludge. More attention should be paid to sewage treatment process decision of WWTP for the control of PFASs.

HRCT1, negatively regulated by miR-124-3p, promotes tumor metastasis and the growth of gastric cancer by activating the ERBB2-MAPK pathway

BACKGROUND

Gastric cancer is the fourth leading cause of cancer-related deaths worldwide. And patient outcomes are poor due to tumor relapse and metastasis. To develop new therapeutic strategies, it is of great importance to explore the mechanism underlying the progression of gastric cancer.

METHODS

Primary gastric cancer samples with lymph node metastases (LNM) and without LNM were subjected to mRNA microarray assay. The differentially expressed genes were confirmed by RT-qPCR. HRCT1 protein expression was further detected using an immunohistochemistry (IHC) assay. In vitro and in vivo assays were performed to investigate the role of HRCT1 in tumor invasion, metastasis, and proliferation. The expressions of the downstream target genes of HRCT1 were detected by microarray, RT-qPCR and Western blot assays. Dual-luciferase reporter and Western blot assays were carried out to identify miRNAs target to HRCT1.

RESULTS

HRCT1 was upregulated in gastric cancer, and high expression of HRCT1 was associated with poor overall survival (OS) and disease-free survival (DFS). Moreover, HRCT1protein expression was an independent predictor for poor OS and DFS. HRCT1 could promote gastric cancer cells' migration, invasion, and proliferation in vitro as well as tumor metastasis and growth in vivo. Notably, our data showed that HRCT1 promoted gastric cancer progression by activating the ERBB2-MAPK signaling pathway. At least partially, the expression of HRCT1 could be negatively regulated by miR-124-3p.

CONCLUSIONS

The upregulated expression of HRCT1 predicts poor survival for patients with gastric cancer. HRCT1 promotes tumor progression by activating the ERBB2-MAPK pathway. HRCT1, negatively regulated by miR-124-3p, may be a potential therapeutic target for patients with gastric cancer.

Assessing the Mass Concentration of Microplastics and Nanoplastics in Wastewater Treatment Plants by Pyrolysis Gas Chromatography-Mass Spectrometry

The level of microplastics (MPs) in wastewater treatment plants (WWTPs) has been well evaluated by the particle number, while the mass concentration of MPs and especially nanoplastics (NPs) remains unclear. In this study, pyrolysis gas chromatography-mass spectrometry was used to determine the mass concentrations of MPs and NPs with different size ranges (0.01-1, 1-50, and 50-1000 μm) across the whole treatment schemes in two WWTPs. The mass concentrations of total MPs and NPs decreased from 26.23 and 11.28 μg/L in the influent to 1.75 and 0.71 μg/L in the effluent, with removal rates of 93.3 and 93.7% in plants A and B, respectively. The proportions of NPs (0.01-1 μm) were 12.0-17.9 and 5.6-19.5% in plants A and B, respectively, and the removal efficiency of NPs was lower than that of MPs (>1 μm). Based on annual wastewater effluent discharge, it is estimated that about 0.321 and 0.052 tons of MPs and NPs were released into the river each year. Overall, this study investigated the mass concentration of MPs and NPs with a wide size range of 0.01-1000 μm in wastewater, which provided valuable information regarding the pollution level and distribution characteristics of MPs, especially NPs, in WWTPs.

One-Dimensional π-d Conjugated Conductive Metal-Organic Framework with Dual Redox-Active Sites for High-Capacity and Durable Cathodes for Aqueous Zinc Batteries

Aqueous Zn-based batteries (ZIBs) possess huge advantages in terms of high safety, low cost, and environmental friendliness. However, the lack of suitable cathodes with high-capacity, long-cycling, and high-rate capability limits their practical application. Herein, we present a highly crystalline one-dimensional π-d conjugated conductive metal-organic framework by coordinating ultrasmall 1,2,4,5-benzenetetramine (BTA) linkers with copper ions (Cu-BTA-H), as a cathode for ZIBs. The large ratio of active sites and dual redox mechanism of Cu-BTA-H, including the one-electron-redox reaction over copper ions (via Cu²⁺/Cu⁺) and the two-electron-redox reaction over organic ligands (via C═N/C-N), effectively enhance its reversible capacity. Meanwhile, the abundant porosity, small band gap, high crystallinity, and stable coordination structure of Cu-BTA-H endow it with fast ion/electron transport and effectively hinder the dissolution of organic ligands during cycling, respectively. Consequently, Cu-BTA-H possesses a high reversible capacity of 330 mAh g^-1 at 200 mA g^-1 and excellent rate performance and long-cycle stability, with a high capacity of 106.1 mAh g^-1 at 2.0 A g^-1 after 500 cycles and a high Coulombic efficiency of ∼100%. The proposed conductive MOFs with dual redox-active sites provide an efficient approach for constructing fast, stable, and high-capacity energy storage devices.

Robust Carbon Nitride Homojunction Photoelectrode for Solar-Driven Water Splitting

Achieving intimate particle-to-particle and particle-to-substrate contacts is the first priority for fabricating high-quality photoelectrodes to ensure sufficient visible light absorption and efficient charge separation/transport. To achieve this goal, a seeding strategy is designed to construct a robust carbon nitride (CN) homojunction photoelectrode, in which vaporized precursors are condensed into a compact seeding layer at low temperatures, inducing the further deposition of the top layer. This optimized photoelectrode displays an excellent photocurrent density of 320 μA cm^-2 in 0.1 M NaOH electrolyte at 1.23 V_RHE (V vs reversible hydrogen electrode) under AM 1.5G illumination, with H₂ and O₂ evolution rates of 2.98 and 1.47 μmol h^-1 cm^-2, respectively. Characterizations show that both the robust contact and the homojunction of the double-layered CN film contribute to enhanced photoelectrochemical performance. This work may provide a new strategy for the design of high-performing CN photoelectrodes.

Development and validation of risk prediction models for stroke and mortality among patients with type 2 diabetes in northern China

BACKGROUND

Stroke is one of the leading causes of disability and mortality in patients with type 2 diabetes mellitus (T2DM). Risk models have been developed for predicting stroke and stroke-associated mortality among patients with T2DM. Here, we evaluated risk factors of stroke for individualized prevention measures in patients with T2DM in northern China.

METHODS

In the community-based Tianjin Chronic Disease Cohort study, 58,042 patients were enrolled between January 2014 and December 2019. We used multiple imputation (MI) to impute missing variables and univariate and multivariate Cox's proportional hazard regression to screen risk factors of stroke. Furthermore, we established and validated first-ever prediction models for stroke (Model 1 and Model 2) and death from stroke (Model 3) and evaluated their performance.

RESULTS

In the derivation and validation groups, the area under the curves (AUCs) of Models 1-3 was better at 5 years than at 8 years. The Harrell's C-index for all models was above 0.7. All models had good calibration, discrimination, and clinical net benefit. Sensitivity analysis using the MI dataset indicated that all models had good and stable prediction performance.

CONCLUSION

In this study, we developed and validated first-ever risk prediction models for stroke and death from stroke in patients with T2DM, with good discrimination and calibration observed in all models. Based on lifestyle, demographic characteristics, and laboratory examination, these models could provide multidimensional management and individualized risk assessment. However, the models developed here may only be applicable to Han Chinese.

Efficacy and safety of endothelin receptor antagonists, phosphodiesterase type 5 Inhibitors, and prostaglandins in pediatric pulmonary arterial hypertension: A network meta-analysis

Background

Pulmonary arterial hypertension (PAH) is a fatal disease characterized by pulmonary vascular remodeling and increased pulmonary artery pressure, leading to impaired lung oxygenation, right heart failure, and even death. Although great advances have been made in PAH-targeted medications for pediatric patients, the efficacy and safety of these treatments are controversial.

Methods

We retrieved relevant articles from electronic databases including PubMed, EMBASE, Web of Science, and Cochrane Library until 12 April 2022. To compare the effectiveness and safety of endothelin receptor antagonists (ERAs), phosphodiesterase type 5 Inhibitors (PDE-5i), and prostaglandins (ProA) in the treatment of pediatric PAH, we investigated six hemodynamic parameters, four respiratory parameters, intensive care unit (ICU) stay duration, length of hospital stay, and two safety outcomes.

Results

A total of 27 randomized controlled trials (RCTs) were included in the meta-analysis with 1,574 pediatric participants. The duration of mechanical ventilation was shorter for patients using bosentan, sildenafil, and ProsA, compared with that for patients using the placebo. Bosentan helped to shorten more time for mechanical ventilation than ProsA did, while ProsA was more effective than sildenafil in this respect. As for the length of stay in the ICU, patients administered by ProsA or sildenafil needed shorter ICU stay, compared to those using the placebo, while ProsA was more effective for shortening ICU stay time. In light of safety outcomes, there was a statistically significant difference between the sildenafil and the placebo group. Sildenafil surpassed ProsA in reducing the incidence of pulmonary hypertension (PH) crisis.

Conclusions

ERAs were more effective than ProsA in shortening the duration of mechanical ventilation, while ProsA were better for shortening the duration of mechanical ventilation and ICU stay than PDE-5i. PDE-5i were found to generate more benefits in decreasing the occurrence of PH crisis, though further investigation is warranted.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=351505.

Within-job gender pay inequality in 15 countries

Extant research on the gender pay gap suggests that men and women who do the same work for the same employer receive similar pay, so that processes sorting people into jobs are thought to account for the vast majority of the pay gap. Data that can identify women and men who do the same work for the same employer are rare, and research informing this crucial aspect of gender differences in pay is several decades old and from a limited number of countries. Here, using recent linked employer-employee data from 15 countries, we show that the processes sorting people into different jobs account for substantially less of the gender pay differences than was previously believed and that within-job pay differences remain consequential.

Understanding consumers' continuance intention to watch streams: A value-based continuance intention model

Introduction

Live stream-watching has become increasingly popular worldwide. Consumers are found to watch streams in a continuous manner. Despite its popularity, there has been limited research investigating why consumers continue to watch streams. Previously, the expectation-confirmation theory (ECT) has been widely adopted to explain users' continuance intention. However, most current ECT-based models are theoretically incomplete, since they only consider the importance of perceived benefits without considering users' costs and sacrifices. In this paper, we propose a value-based continuance intention model (called V-ECM), and use it to investigate factors influencing consumers' continuance intention to watch streams.

Methods

Our hypotheses were tested using an online survey of 1,220 consumers with continuance stream-watching experiences.

Results

Results indicate that perceived value, a process of an overall assessment between users' perceived benefits and perceived sacrifices, is proved to be a better variable than perceived benefits in determining consumers' continuance watching intention. Also, compared with other ECT-based models, V-ECM is a more comprehensive model to explain and predict consumers' continuance intention.

Discussion

V-ECM theoretically extends ECT-based studies, and it has potential to explain and predict other continuance intentions in online or technology-related contexts. In addition, this paper also discusses practical implications for live streaming platforms with regards to their design, functions and marketing.

Pathophysiological roles of integrins in gliomas from the perspective of glioma stem cells

Glioblastoma is the most common primary intracranial tumor and is also one of the most malignant central nervous system tumors. Its characteristics, such as high malignancy, abundant tumor vasculature, drug resistance, and recurrence-prone nature, cause great suffering to glioma patients. Furthermore, glioma stem cells are the primordial cells of the glioma and play a central role in the development of glioma. Integrins—heterodimers composed of noncovalently bound a and ß subunits—are highly expressed in glioma stem cells and play an essential role in the self-renewal, differentiation, high drug resistance, and chemo-radiotherapy resistance of glioma stem cells through cell adhesion and signaling. However, there are various types of integrins, and their mechanisms of function on glioma stem cells are complex. Therefore, this article reviews the feasibility of treating gliomas by targeting integrins on glioma stem cells.

Electrocatalytic Oxygen Reduction to Produce Hydrogen Peroxide: Rational Design from Single-Atom Catalysts to Devices

Electrocatalytic production of hydrogen peroxide (H2O2) via the 2e- transfer route of the oxygen reduction reaction (ORR) offers a promising alternative to the energy-intensive anthraquinone process, which dominates current industrial-scale production of H2O2. The availability of cost-effective electrocatalysts exhibiting high activity, selectivity, and stability is imperative for the practical deployment of this process. Single-atom catalysts (SACs) featuring the characteristics of both homogeneous and heterogeneous catalysts are particularly well suited for H2O2 synthesis and thus, have been intensively investigated in the last few years. Herein, we present an in-depth review of the current trends for designing SACs for H2O2 production via the 2e- ORR route. We start from the electronic and geometric structures of SACs. Then, strategies for regulating these isolated metal sites and their coordination environments are presented in detail, since these fundamentally determine electrocatalytic performance. Subsequently, correlations between electronic structures and electrocatalytic performance of the materials are discussed. Furthermore, the factors that potentially impact the performance of SACs in H2O2 production are summarized. Finally, the challenges and opportunities for rational design of more targeted H2O2-producing SACs are highlighted. We hope this review will present the latest developments in this area and shed light on the design of advanced materials for electrochemical energy conversion.

Graphical abstract

An Ultrahigh Rate and Stable Zinc Anode by Facet-Matching-Induced Dendrite Regulation

Resource-abundant metal (e.g., zinc) batteries feature intrinsic advantages of safety and sustainability. Their practical feasibility, however, is impeded by the poor reversibility of metal anodes, typically caused by the uncontrollable dendrite enlargement. Significant effort is exerted to completely prevent dendrites from forming, but this seems less effective at high current densities. Herein, this work presents an alternative dendrite regulation strategy of forming tiny, homogeneously distributed, and identical zinc dendrites by facet matching, which effectively avoids undesirable dendrite enlargement. Confirmed by multiscale theoretical screening and characterization, the regularly exposed Cu(111) facets at the ridges of a copper nanowire are capable of such dendrite regulation by forming a low-mismatched Zn(002)/Cu(111) interface. Consequently, reversible zinc electroplating/stripping is achieved at an unprecedentedly high rate of 100 mA cm^-2 for over 30 000 cycles, corresponding to an accumulative areal capacity up to 30 Ah cm^-2 . A full cell using this anode shows a high capacity of 308.3 mAh g^-1 and a high capacity retention of 91.4% after 800 cycles. This strategy is also viable for magnesium and aluminum anodes, thus opening up a promising and universal avenue toward long-life and high-rate metal anodes.

A computed tomography-based radiomics signature for predicting expression of programmed death ligand 1 in head and neck squamous cell carcinoma

OBJECTIVES

Accurate prediction of the expression of programmed death ligand 1 (PD-L1) in head and neck squamous cell carcinoma (HNSCC) before immunotherapy is crucial. This study was performed to construct and validate a contrast-enhanced computed tomography (CECT)-based radiomics signature to predict the expression of PD-L1 in HNSCC.

METHODS

In total, 157 patients with confirmed HNSCC who underwent CECT scans and immunohistochemical examination of tumor PD-L1 expression were enrolled in this study. The patients were divided into a training set (n = 104; 62 PD-L1-positive and 42 PD-L1-negative) and an external validation set (n = 53; 34 PD-L1-positive and 19 PD-L1-negative). A radiomics signature was constructed from radiomics features extracted from the CECT images, and a radiomics score was calculated. Performance of the radiomics signature was assessed using receiver operating characteristics analysis.

RESULTS

Nine features were finally selected to construct the radiomics signature. The performance of the radiomics signature to distinguish between a PD-L1-positive and PD-L1-negative status in both the training and validation sets was good, with an area under the receiver operating characteristics curve of 0.852 and 0.802 for the training and validation sets, respectively.

CONCLUSIONS

A CECT-based radiomics signature was constructed to predict the expression of PD-L1 in HNSCC. This model showed favorable predictive efficacy and might be useful for identifying patients with HNSCC who can benefit from anti-PD-L1 immunotherapy.

KEY POINTS

• Accurate prediction of the expression of PD-L1 in HNSCC before immunotherapy is crucial. • A CECT-based radiomics signature showed favorable predictive efficacy in estimation of the PD-L1 expression status in patients with HNSCC.

Deep Learning Radiomics Nomogram to Predict Lung Metastasis in Soft-Tissue Sarcoma: A Multi-Center Study

Objectives

To build and evaluate a deep learning radiomics nomogram (DLRN) for preoperative prediction of lung metastasis (LM) status in patients with soft tissue sarcoma (STS).

Methods

In total, 242 patients with STS (training set, n=116; external validation set, n=126) who underwent magnetic resonance imaging were retrospectively enrolled in this study. We identified independent predictors for LM-status and evaluated their performance. The minimum redundancy maximum relevance (mRMR) method and least absolute shrinkage and selection operator (LASSO) algorithm were adopted to screen radiomics features. Logistic regression, decision tree, random forest, support vector machine (SVM), and adaptive boosting classifiers were compared for their ability to predict LM. To overcome the imbalanced distribution of the LM data, we retrained each machine-learning classifier using the synthetic minority over-sampling technique (SMOTE). A DLRN combining the independent clinical predictors with the best performing radiomics prediction signature (mRMR+LASSO+SVM+SMOTE) was established. Area under the receiver operating characteristics curve (AUC), calibration curves, and decision curve analysis (DCA) were used to assess the performance and clinical applicability of the models.

Result

Comparisons of the AUC values applied to the external validation set revealed that the DLRN model (AUC=0.833) showed better prediction performance than the clinical model (AUC=0.664) and radiomics model (AUC=0.799). The calibration curves indicated good calibration efficiency and the DCA showed the DLRN model to have greater clinical applicability than the other two models.

Conclusion

The DLRN was shown to be an accurate and efficient tool for LM-status prediction in STS.

Multi-parametric MRI-based radiomics signature for preoperative prediction of Ki-67 proliferation status in sinonasal malignancies: a two-centre study

OBJECTIVE

To assess the predictive ability of a multi-parametric MRI-based radiomics signature (RS) for the preoperative evaluation of Ki-67 proliferation status in sinonasal malignancies.

METHODS

A total of 128 patients with sinonasal malignancies that underwent multi-parametric MRIs at two medical centres were retrospectively analysed. Data from one medical centre (n = 77) were used to develop the predictive models and data from the other medical centre (n = 51) constitute the test dataset. Clinical data and conventional MRI findings were reviewed to identify significant predictors. Radiomics features were determined using maximum relevance minimum redundancy and least absolute shrinkage and selection operator algorithms. Subsequently, RSs were established using a logistic regression (LR) algorithm. The predictive performance of RSs was assessed using calibration, decision curve analysis (DCA), accuracy, and AUC.

RESULTS

No independent predictors of high Ki-67 proliferation were observed based on clinical data and conventional MRI findings. RS-T1, RS-T2, and RS-T1c (contrast enhancement T1WI) were established based on a single-parametric MRI. RS-Combined (combining T1WI, FS-T2WI, and T1c features) was developed based on multi-parametric MRI and achieved an AUC and accuracy of 0.852 (0.733-0.971) and 86.3%, respectively, on the test dataset. The calibration curve and DCA demonstrated an improved fitness and benefits in clinical practice.

CONCLUSIONS

A multi-parametric MRI-based RS may be used as a non-invasive, dependable, and accurate tool for preoperative evaluation of the Ki-67 proliferation status to overcome the sampling bias in sinonasal malignancies.

KEY POINTS

• Multi-parametric MRI-based radiomics signatures (RSs) are used to preoperatively evaluate the proliferation status of Ki-67 in sinonasal malignancies. • Radiomics features are determined using maximum relevance minimum redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) algorithms. • RSs are established using a logistic regression (LR) algorithm.

Hundred-gram scale fabrication of few-layered silicene by a continuous vapor-dealloying strategy for high-performance lithium storage

A continuous vapor de-alloying strategy for a hundred-gram scale fabrication of silicene is developed by etching CaSi₂ using waste polyvinyl chloride (PVC). The as-obtained few-layered silicene can be readily assembled with carbon nanotubes into flexible electrodes for lithium storage with excellent performance, which stably deliver a high capacity and stability. This strategy can be extended to other silicon analogs with various structures by selecting precursors such as Mg₂Si and Al/Si alloy.

Preparation and Properties of Highly Elastic, Lightweight, and Thermally Insulating SiO2 Fibrous Porous Materials

Fibrous porous materials are one of the most commonly used high-temperature insulation materials because of their high porosity and low thermal conductivity. Due to their wide applications in the aerospace and energy industries, the investigation of high-elastic thermally insulating porous materials has attracted increasing attention. In order to improve the elasticity of fibrous porous materials, quartz fibers with high aspect ratio were used as matrix, sodium hexametaphosphate (SHMP) was selected as dispersant. We innovatively reported that a unique three-dimensional skeleton structure was constructed by adjusting the dispersion of fibers in the slurry, and the lightweight, thermal insulating and elastic SiO₂ fibrous porous material was then prepared by the compression molding method. The characterization results of zeta potential and absorbance showed that the addition of SHMP was an effective method to enhance the dispersibility of quartz fibers in the slurry. SiO₂ fibrous porous materials with 0.4 wt% SHMP content exhibited an ideal three-dimensional skeleton structure, which endowed the porous material with high porosity (89.39%), low density (0.04751 g/cm³), and low thermal conductivity (0.0356 W·m⁻¹·K⁻¹). The three-dimensional skeleton structure formed by overlapping fibers with high aspect ratios endowed the porous material with excellent elasticity. SiO₂ fibrous porous materials with 0.4 wt% SHMP content could undergo large strains of 30% and achieved a resilience ratio of 81.69% under the 30th compression cycle. Moreover, after heat treatment at 800 °C, SiO₂ fibrous porous materials also maintained good elasticity with a resilience ratio of more than 80%.

Pilot-scale demonstration of a novel process integrating Partial Nitritation with simultaneous Anammox, Denitrification and Sludge Fermentation (PN + ADSF) for nitrogen removal and sludge reduction

Anammox process is a cost-effective solution for nitrogen removal, whereas unsatisfactory effluent with nitrate accumulation is usually achieved in treating domestic sewage, owning to the unwanted prevalence of nitrite-oxidizing bacteria (NOB) and the intrinsic nitrate production by anammox bacteria. Herein, a pilot-scale system integrating Partial Nitritation and simultaneous Anammox, Denitrification and Sludge Fermentation (PN + ADSF) process was developed to treat real municipal wastewater. In this process, PN was accomplished in a sequencing batch reactor (SBR) using the strategy of intermittent hydroxylamine addition, while ADSF coupling anammox and heterotrophic denitrification was conducted in an up-flow anaerobic sludge blanket reactor (UASB) to further remove nitrogen. The pilot-scale system achieved total inorganic nitrogen (TIN) concentrations of 10.0 mg N/L in effluent and sludge reduction efficiency of 42.3% simultaneously. The characterization on microbial communities revealed that Candidatus Kuenenia and Thauera were the dominant functional bacteria for anammox and denitrification, respectively. Supported by the slow-release carbon sources from sludge fermentation, heterotrophic denitrification contributed to about 28% of nitrogen removed from the UASB, while anammox played a more important role in nitrogen removal. The pilot-scale demonstration confirmed that the PN + ADSF process is technically feasible for enhanced nitrogen removal and sludge reduction.

Differential diagnosis of renal oncocytoma and chromophobe renal cell carcinoma using CT features: a central scar-matched retrospective study

BACKGROUND

Renal oncocytoma (RO) and chromophobe renal cell carcinoma (chRCC) have a common cellular origin and different clinical management and prognosis.

PURPOSE

To explore the utility of computed tomography (CT) in the differentiation of RO and chRCC.

MATERIAL AND METHODS

Twenty-five patients with RO and 73 patients with chRCC presenting with the central scar were included retrospectively. Two experienced radiologists independently reviewed the CT imaging features, including location, tumor size, relative density ratio, segmental enhancement inversion (SEI), necrosis, and perirenal fascia thickening, among others. Interclass correlation coefficient (ICC, for continuous variables) or Kappa coefficient test (for categorical variables) was used to determine intra-observer and inter-observer bias between the two radiologists.

RESULTS

The inter- and intra-reader reproducibility of the other CT imaging parameters were nearly perfect (>0.81) except for the measurements of fat (0.662). RO differed from chRCC in the cortical or medullary side (P = 0.005), relative density ratio (P = 0.020), SEI (P < 0.001), and necrosis (P = 0.045). The logistic regression model showed that location (right kidney), hypo-density on non-enhanced CT, SEI, and perirenal fascia thickening were highly predictive of RO. The combined indicators from logistic regression model were used for ROC analysis. The area under the ROC curve was 0.923 (P < 0.001). The sensitivity and specificity of the four factors combined for diagnosing RO were 88% and 86.3%, respectively. The correlation coefficient between necrosis and tumor size in all tumors including both of RO and chRCC was 0.584, indicating a positive correlation (P < 0.001).

CONCLUSION

The CT imaging features of location (right kidney), hypo-density on non-enhanced CT, SEI, and perirenal fascia thickening were valuable indicators in distinguishing RO from chRCC.

A CT-based radiomics signature for preoperative discrimination between high and low expression of programmed death ligand 1 in head and neck squamous cell carcinoma

PURPOSE

Accurate prediction of the expression level of programmed death ligand 1 (PD-L1) in head and neck squamous cell carcinoma (HNSCC) is crucial before immunotherapy. The purpose of this study was to construct and validate a contrast-enhanced computed tomography (CECT)-based radiomics signature to discriminate between high and low expression status of PD-L1.

METHODS

A total of 179 HNSCC patients who underwent immunohistochemical examination of tumor PD-L1 expression at one of two centers were enrolled in this study and divided into a training set (n = 122; 55 high PD-L1 expression and 67 low PD-L1 expression) and an external validation set (n = 57; 26 high PD-L1 expression and 31 low PD-L1 expression). The least absolute shrinkage and selection operator method was used to select the key features for a CECT-image-based radiomics signature. The performance of the radiomics signature was assessed using receiver operating characteristics analysis.

RESULTS

Six features were finally selected to construct the radiomics signature. The performance of the radiomics signature in the discrimination between high and low PD-L1 expression status was good in both the training and validation sets, with areas under the receiver operating characteristics curve of 0.889 and 0.834 for the training and validation sets, respectively.

CONCLUSIONS

The constructed CECT-based radiomics signature model showed favorable performance for discriminating between high and low PD-L1 expression status in HNSCC patients. It may be useful for screening out those patients with HNSCC who can best benefit from anti-PD-L1 immunotherapy.

Resection of a giant sternal chondrosarcoma and chest wall reconstruction: a case report

Chondrosarcomas are common bone carcinomas; however, they are uncommon in the sternum, and giant sternal tumors have rarely been reported in advanced-age patients. This study aimed to describe the clinical presentation, method of preoperative planning and surgery, and perioperative management of a giant sternal chondrosarcoma in an advanced-age patient. We describe the case of an 80-year-old woman who presented with a rare giant sternal chondrosarcoma. The patient’s symptoms included significant painful swelling and limited activity. The mass was firm and fixed, and the boundary was unclear. We first performed a simulated surgery on a three-dimensional (3D) model using the mimics system for preoperative planning. An extensive resection of the tumor was then performed. Due to the financial status of the patient, the huge chest wall defect was reconstructed with simple ordinary metal locking bone plates and polyester surgical mesh, and good results were achieved. The patient was discharged without any complications 12 days after surgery. The postoperative pathological examination confirmed the diagnosis of primary grade I–II chondrosarcoma. At the 12-month follow-up examination, the patient was completely rehabilitated, and there was no evidence of recurrence. Giant, low-grade sternal chondrosarcoma is an extremely rare disease in elderly women. 3D modeling and simulated surgery are effective approaches for the preoperative planning of surgery. Postoperative ventilators, antibiotics, and nutritional support are also necessary. Using our reconstructive techniques, chest wall reconstruction with polyester patches and orthopedic steel plates could be a safe, reliable and affordable surgery procedure. It may be an appropriate option for similar cases.

Photoluminescence and magnetism integrated multifunctional black phosphorus probes through controllable PO bond orbital hybridization

Biological probes with integrated photoluminescence and magnetism characteristics play a critical role in modern clinical diagnosis and surgical protocols combining fluorescence optical imaging (FOI) with magnetic resonance imaging (MRI) technology. However, traditional magnetic semiconductors can easily generate a spin splitting at the Fermi level and half-metallic electronic occupation, which will sharply reduce the radiation recombination efficiency of photogenerated carriers. To overcome this intrinsic contradiction, we propose a controllable oxidation strategy to introduce some particular PO bonds into black phosphorus nanosheets, in which the p orbital hybridization between P and O atoms not only provides some carrier recombination centers but also leads to a room-temperature spin polarization. As a result, the coexistence of photoluminescence and magnetism is realized in multifunctional black phosphorus probes with excellent biocompatibility. This work provides a new insight into integrating photoluminescence and magnetism together by intriguing atomic orbital hybridization.

Structural and functional characterization of ubiquitin variant inhibitors for the JAMM-family deubiquitinases STAMBP and STAMBPL1

Ubiquitination is a crucial posttranslational protein modification involved in a myriad of biological pathways. This modification is reversed by deubiquitinases (DUBs) that deconjugate the single ubiquitin (Ub) moiety or poly-Ub chains from substrates. In the past decade, tremendous efforts have been focused on targeting DUBs for drug discovery. However, most chemical compounds with inhibitory activity for DUBs suffer from mild potency and low selectivity. To overcome these obstacles, we developed a phage display-based protein engineering strategy for generating Ub variant (UbV) inhibitors, which was previously successfully applied to the Ub-specific protease (USP) family of cysteine proteases. In this work, we leveraged the UbV platform to selectively target STAMBP, a member of the JAB1/MPN/MOV34 (JAMM) metalloprotease family of DUB enzymes. We identified two UbVs (UbVSP.1 and UbVSP.3) that bind to STAMBP with high affinity but differ in their selectivity for the closely related paralog STAMBPL1. We determined the STAMBPL1-UbVSP.1 complex structure by X-ray crystallography, revealing hotspots of the JAMM-UbV interaction. Finally, we show that UbVSP.1 and UbVSP.3 are potent inhibitors of STAMBP isopeptidase activity, far exceeding the reported small-molecule inhibitor BC-1471. This work demonstrates that UbV technology is suitable to develop molecules as tools to target metalloproteases, which can be used to further understand the cellular function of JAMM family DUBs.

Cu-Ion-Implanted and Polymeric Carbon Nitride-Decorated TiO2 Nanotube Array for Unassisted Photoelectrochemical Water Splitting

Photoelectrochemical (PEC) water splitting over TiO₂ photoanodes is a promising strategy for hydrogen production due to its eco-friendly, energy-saving, and low-cost nature. However, the intrinsic drawbacks of TiO₂, i.e., the too wide band gap and rapid exciton recombination, significantly limit further enhancement of its performance. Herein, we report a TiO₂ nanotube array (TNA), which is implanted by Cu ions and decorated by polymeric carbon nitride (PCN) nanosheets, as a photoanode for the high-efficiency PEC water splitting. In such designed material, Cu-ion implantation can effectively tailor the electronic structure of TiO₂, thus narrowing the band gap and enhancing the electronic conductivity. Meanwhile, the PCN decoration induces TiO₂/PCN heterojunctions, enhancing the visible light absorption and accelerating the exciton separation. Upon this synergistic effect, the modified TNA photoanode shows significantly improved PEC capability. Its photocurrent density, solar-to-hydrogen efficiency, and applied bias photon-to-current efficiency achieve 1.89 mA cm^-2 at 1.23 V_RHE (V vs reversible hydrogen electrode), 2.31%, and 1.20% at 0.46 V_RHE, respectively. Importantly, this modified TNA supported on a meshlike Ti substrate can be readily integrated with a perovskite solar cell to realize unassisted PEC water splitting.

New Equivalent Thermal Conductivity Model for Size-Dependent Convection-Driven Melting of Spherically Encapsulated Phase Change Material

Spherically encapsulated phase change materials (PCMs) are extensively incorporated into matrix material to form composite latent heat storage system for the purposes of saving energy, reducing PCM cost and decreasing space occupation. Although the melting of PCM sphere has been studied comprehensively by experimental and numerical methods, it is still challenging to quantitatively depict the contribution of complex natural convection (NC) to the melting process in a practically simple and acceptable way. To tackle this, a new effective thermal conductivity model is proposed in this work by focusing on the total melting time (TMT) of PCM, instead of tracking the complex evolution of solid-liquid interface. Firstly, the experiment and finite element simulation of the constrained and unconstrained meltings of paraffin sphere are conducted to provide a deep understanding of the NC-driven melting mechanism and exhibit the difference of melting process. Then the dependence of NC on the particle size and heating temperature is numerically investigated for the unconstrained melting which is closer to the real-life physics than the constrained melting. Subsequently, the contribution of NC to the TMT is approximately represented by a simple effective thermal conductivity correlation, through which the melting process of PCM is simplified to involve heat conduction only. The effectiveness of the equivalent thermal conductivity model is demonstrated by rigorous numerical analysis involving NC-driven melting. By addressing the TMT, the present correlation thoroughly avoids tracking the complex evolution of melting front and would bring great convenience to engineering applications.

VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images

Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit clinical decision support systems for diagnosis, surgery planning, and population-based analysis of spine and bone health. However, designing automated algorithms for spine processing is challenging predominantly due to considerable variations in anatomy and acquisition protocols and due to a severe shortage of publicly available data. Addressing these limitations, the Large Scale Vertebrae Segmentation Challenge (VerSe) was organised in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) in 2019 and 2020, with a call for algorithms tackling the labelling and segmentation of vertebrae. Two datasets containing a total of 374 multi-detector CT scans from 355 patients were prepared and 4505 vertebrae have individually been annotated at voxel level by a human-machine hybrid algorithm (https://osf.io/nqjyw/, https://osf.io/t98fz/). A total of 25 algorithms were benchmarked on these datasets. In this work, we present the results of this evaluation and further investigate the performance variation at the vertebra level, scan level, and different fields of view. We also evaluate the generalisability of the approaches to an implicit domain shift in data by evaluating the top-performing algorithms of one challenge iteration on data from the other iteration. The principal takeaway from VerSe: the performance of an algorithm in labelling and segmenting a spine scan hinges on its ability to correctly identify vertebrae in cases of rare anatomical variations. The VerSe content and code can be accessed at: https://github.com/anjany/verse.

Acute myeloid leukemia with T lymphoblastic lymphoma: a case report and literature review

Acute myeloid leukemia (AML) with T lymphoblastic lymphoma (T-LBL) is a hematologic tumor of two origins, myeloid and lymphoblastic, and is relatively rare in the same patient. We report a rare case of AML with T-LBL. After the patient was diagnosed, he received standard chemotherapy, which decreased the primitive bone marrow cell percentage from 84% to 5%; however, the enlarged superficial lymph nodes showed no obvious change in size. Immunohistochemistry revealed the following: cluster of differentiation (CD)3 (+), CD5 (+), CD7 (+), transmission disequilibrium test (TDT) (+), myeloperoxidase (MPO) (-), and lysozyme (Lys) (-). The lymph node morphology and immunohistochemical results indicated T-LBL. Therefore, the final diagnosis was AML with T-LBL, with both diseases occurring independently and concurrently.