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Abstract In the process of penicillin fermentation, there is a strong nonlinear relationship between the input eigenvector and multiple output vectors, which makes the prediction accuracy of the existing model difficult to meet the requirements of chemical production. Therefore, a local selective ensemble learning multi-objective soft sensing modeling strategy is proposed in this study. Firstly, a localization method based on transfer entropy and k-means is proposed to reconstruct the sample set. Then, based on the reconstructed local samples, the local soft sensing model is established by the multi-objective support vector regression method, and the selective ensemble of sub-models and the adaptive calculation of prediction weights are realized. At the same time, to reduce the adverse effects caused by improper selection of model parameters, the sparrow search algorithm is used to realize the tuning of the mentioned model parameters. Finally, the proposed modeling strategy is simulated. The results show that, compared with other methods, the proposed local selective ensemble learning multi-objective soft sensing modeling strategy has better prediction performance.

This is an article in the field of ceramics and composites. Hydroxyapatite (HAP) has excellent ion exchange performance, shows good adsorption capacity for heavy metal ions, harmful anions, and organics in wastewater, and will not cause secondary pollution in the process of wastewater treatment. Thus, it is a promising green adsorbent. Due to its small size and large specific surface area, nano-hydroxyapatite (nHAP) exposes more adsorption sites, showing supreme adsorption capacity. It is a tendency to produce nHAP composites of strong adsorption capacity, easy for solid-liquid separation and regeneration, and low-cost. This article reviews the recent research progress of nano-HAP and its composites as adsorbents for wastewater treatment, and prospects the application of them as adsorbents.

BackgroundNumerous studies have suggested a link between dietary micronutrient intake and the onset of constipation. Nevertheless, there has not been much research done on the potential relationship between vitamin B6 and constipation. The purpose of this study was to determine whether dietary vitamin B6 consumption and chronic constipation are related among adult participants in the National Health and Nutrition Examination Survey (NHANES).MethodThe study made use of information from the 2009–2010 NHANES health and nutrition survey. Respondents’ dietary information was gathered using 24-h dietary recalls. A range of statistical techniques, including as interaction tests, subgroup analyses, and curve fitting analyses, were used to examine the connection between dietary vitamin B6 intake and chronic constipation.ResultThis study included 3,643 patients, with 270 (7.41%) diagnosed with persistent constipation. A fully adjusted multiple logistic regression analysis found that increasing dietary vitamin B6 consumption (OR = 0.78, 95% CI: 0.68–0.89) was linked to a lower incidence of constipation, with significance at p

IntroductionJacaranda mimosifolia, native to South America, is a notable ornamental tree widely used in Chinese urban landscaping due to its aesthetic and environmental value. Despite its popularity, the cultivation of J. mimosifolia in China faces challenges, including intermittent failures in various regions. This study assesses the potential distribution of J. mimosifolia in China and its response to climate change, providing insights for its application and promotion.MethodsUsing MaxEnt software, we developed an ecological niche model from 218 distribution records and selected 10 environmental variables to predict the tree’s distribution under various climate scenarios (SSP126, SSP245, SSP370).ResultsOur model demonstrates high predictive accuracy (AUC > 0.90) across scenarios, identifying key factors such as the mean temperature of the coldest quarter (bio11), precipitation of the driest month (bio14), temperature annual range (bio7), and minimum temperature of the coldest month (bio6). Their relative contribution rates were 49.3%, 18.4%, 15.6%, and 2.0%, respectively. The average temperature of the coldest quarter was not lower than 5°C, with the ideal range being 7.38~14.88°C. Currently, J. mimosifolia predominantly thrives in Taiwan, Fujian, Guangdong, Hainan, Guangxi, Yunnan, and to a lesser extent in the Sichuan Basin, southern Guizhou, Tibet, Hunan, Jiangxi, and Zhejiang province, covering a total area of approximately 122.19 × 104 km2. Future predictions indicate that under the SSP126 scenario, the most significant contraction occurs between the 2050s and 2070s, with a total change of −1.08 × 104 km2. Conversely, under the SSP370 scenario, the greatest expansion is observed from the 2030s to the 2050s, amounting to a change of 2.08 × 104 km2. Suitable area expansion is anticipated in most periods and scenarios, except for SSP126 in the 2070s, SSP245 in the 2050s, and SSP370 in the 2030s and 2070s. The distribution center shifts observed include movements northwestward, southwestward, and eastward with distances ranging from 5.12 km to 18.84 km. These shifts are likely driven by global warming, resulting in movements to higher elevations and latitudes.DiscussionThese predictions will provide a solid theoretical foundation for the future application of J. mimosifolia in urban landscaping and serve as a valuable reference for its introduction and cultivation.

The intelligent mine ventilation system is very important for the intelligent construction of coal mines. In order to solve the problem of missing mine ventilation parameter data caused by the lack of measurement conditions, instrument signal interference, uneven wind speed of roadway section, improper manual operation and other restrictive factors during actual measurement of mine ventilation parameters, a method for filling the missing data of mine ventilation parameters based on the multiple imputation method of random forest-chained equation was proposed. Multiple imputation with chained equations is used to generate n filled values for each missing attribute value by iterations, resulting in n complete datasets, and a final complete dataset is obtained by analyzing and optimizing the n complete datasets. In order to improve the filling accuracy of missing values, the influence of the uncertainty of missing data of mine ventilation parameters on the analysis process is reasonably considered, and the missing data is filled in the prediction task of random forest in combination with the prediction mean matching model. Taking the Luxin No.2 Mine as an experimental example, the intelligent mine ventilation simulation system IMVS was used to preprocess the original data set of ventilation parameters of the Luxin No.2 Mine to obtain a complete and accurate complete dataset of mine ventilation parameters. Comparative experiments with different missing attributes, different data missing rates, and different number of iterations were conducted separately for the complete data set. The effectiveness of the model was evaluated by a variety of model evaluation indicators. The results show that the complete data set formed by the multiple imputation method of random forest-chained equation has good similarity with the original data set. Results of filling experiments with different missing columns show that the filling model can easily handle mixed data types, autonomously learning the correlations between parameters and thus reducing filling complexity. The n datasets formed after iterations are combined into a final dataset by analysis, which improves the filling accuracy. Experiments with different iterations on the complete data set after initial filling show that the data correlation will converge after a certain number of iterations.

During pumped energy storage using abandoned mines, coal pillars are not only affected by monotonic loads, but also suffer from frequent stress disturbances. The strength and deformation characteristics as well as the failure mode of the coal specimens under the influence of monotonic loading (stress path 1), multilevel constant-amplitude cyclic loading (stress path 2) and multilevel increasing cyclic loading (stress path 3) were studied using the coal samples from Hepan Coal Mine, Shaanxi Province, as the research object. The test results showed that the stress-strain curves of the coal specimens under cyclic loading formed obvious hysteresis loops, and the area of hysteresis loops increased significantly with the rise of stress level; compared with the axial strain, the circumstantial strain was more sensitive to the stress path; the peak strength and peak axial strain of the coal samples were the largest under monotonic loading, and the peak strength and axial strain of the specimens decreased by 22.12% and 18.35% (path 2) and 5.30% and 10.34% (path 3) under multi-level cyclic loading, respectively; the tangent modulus of the specimens under stress path 2 was significantly higher than the other stress paths; the stress paths had not changed the macroscopic failure mode of the coal specimens, but the cyclic loading caused the number and size of cracks on the specimen’s surface to become larger.

This is an article in the field of process mineralogy. Systematic process mineralogy study on phosphorus tailings was carried out by using the advanced mineral identification and characterization system (AMICS). The chemical compositions, mineral components, embedded characteristics of minerals, particle size, and the characteristics of liberation degree and the other characteristics were mainly studied. The results show that the gangue minerals are mainly dolomite and quartz. The phosphate mineral is mainly collophane which exists in the form of poor intergrowth. The phosphate mineral is extremely finely disseminated and closely associated with the gangue minerals. This study can provide some guidance for the optimization of phosphate ore dressing and the comprehensive utilization of tailings resources.

In order to control the surrounding rock of deep high-stress roadways, a new prestressed anchor-grouting reinforcement method was proposed with an engineering background of the 1780 ventilation roadway of Shiyakou Coal Mine. A high-fluidity quick-setting micro-expansion (HFQSME) grouting material had been developed through superplasticizer, accelerator, and expansion agent. The results showed that the optimal ratio of HFQSME grouting material was superfine Portland cement of 95 %, superplasticizer of 0.5 %, accelerator agent of 0.5 %, expansion agent of 5.0 %, and water-binder ratio of 0.4. The fluidity, initial setting time and expansion rate of the grouting material were 47 cm, 41 minutes and 0.12 %, respectively. The grouting reinforcement effect of superfine slurry and HFQSME grouting material on rock mass with different degrees of fragmentation was investigated. The peak strength of rock mass with two degrees of fragmentation reinforced by HFQSME grouting material was 166 % and 233 % higher than that of superfine slurry. The macro reinforcement effect of HFQSME grouting material on the surrounding rock of deep high-stress roadway was evaluated through industrial testing. The prestressed anchor grouting method was used to improve the original support design scheme, and data monitoring and analysis were conducted on site. Compared with the original supporting scheme, the deformation of the 1780 ventilation was significantly reduced. Therefore, HFQSME grouting material had good adaptability for the surrounding rock of deep high-stress roadways.

Preclinical models serve as indispensable tools in translational medicine. Specifically, patient-derived models such as patient-derived xenografts (PDX), induced pluripotent stem cells (iPSC), organoids, and recently developed technique of conditional reprogramming (CR) have been employed to reflect the host characteristics of diseases. CR technology involves co-culturing epithelial cells with irradiated Swiss-3T3-J2 mouse fibroblasts (feeder cells) in the presence of a Rho kinase (ROCK) inhibitor, Y-27632. CR technique facilitates the rapid conversion of both normal and malignant cells into a “reprogrammed stem-like” state, marked by robust in vitro proliferation. This is achieved without reliance on exogenous gene expression or viral transfection, while maintaining the genetic profile of the parental cells. So far, CR technology has been used to study biology of diseases, targeted therapies (precision medicine), regenerative medicine, and noninvasive diagnosis and surveillance. Respiratory diseases, ranking as the third leading cause of global mortality, pose a significant burden to healthcare systems worldwide. Given the substantial mortality and morbidity rates of respiratory diseases, efficient and rapid preclinical models are imperative to accurately recapitulate the diverse spectrum of respiratory conditions. In this article, we discuss the applications and future potential of CR technology in modeling various respiratory tract diseases, including lung cancer, respiratory viral infections (such as influenza and Covid-19 and etc.), asthma, cystic fibrosis, respiratory papillomatosis, and upper aerodigestive track tumors. Furthermore, we discuss the potential utility of CR in personalized medicine, regenerative medicine, and clinical translation.

Environmental pollution is widespread and poses significant risks to both human populations and diverse animal species. As part of conservation initiatives, many endangered animals are housed in zoos and breeding centers close to human activities, potentially exposing them to health threats arising from environmental contamination, such as mercury (Hg). By analyzing non-invasive fecal samples from 13 Chinese zoos, we assessed total mercury (THg) and methylmercury (MeHg) exposure in two non-human primate species: the endangered species golden snub-nosed monkey (Rhinopithecus roxellana), and the most widely distributed rhesus macaque (Macaca mulatta). The concentration of THg in golden snub-nosed monkeys (mean ± s.d.: 76.7 ± 35.6 ng/g; median: 71.8 ng/g, range: 11.2–200.0 ng/g, n = 71) was significantly higher than that in rhesus macaques (mean ± s.d.: 32.3 ± 54.7 ng/g; median: 17.5 ng/g, range: 7.4–409.0 ng/g, n = 98). No significant differences were observed in both MeHg and MeHg % between these two species. Age and sex did not predict fecal Hg. Among adults, approximately 85 % of sampled individuals exhibited hazard quotient (HQ) values exceeding 1, indicating mercury poses a health risk to captive primate populations. The average HQ for golden snub-nosed monkeys was 2.98 ± 1.68 (range: 0.46–8.21, n = 43), while for rhesus macaques was 1.84 ± 1.64 (range: 0.61–12.49, n = 71). Our findings suggest that conservation efforts for captive primates may be compromised by Hg pollution, particularly in golden snub-nosed monkeys. Further investigation and ongoing biomonitoring from an ecotoxicological perspective, are crucial to ensuring the health of captive primate populations.

Although the underwater optical communication system (UWOC) plays an important role in many marine applications, the acquisition, pointing and tracking (APT) problems are still great challenges in a long or turbid water channel. The Orthogonal Frequency Division Multiplexing (OFDM) and the space-time block coding (STBC) technologies have been introduced in UWOC systems to improve spectral efficiency and data transmission reliability. On these foundations, a multi-input multi-output (MIMO) mode is proposed and verified in this article to reduce the alignment requirement. In experiments, two sets of 450 nm blue laser diodes (LDs) and PIN photodiodes are selected as light sources and receivers, and then parallel light beams are generated and modulated using an Alamouti coding for its anti-interference ability. The receiving plane is rotated to simulate the various alignment situations, and the system performance of MIMO-OFDM and single-input single-output OFDM (SISO-OFDM) are compared in tap water and turbid water. The results show that the spatial diversity in MIMO can extend the communication range and its single-sided maximum detection angle range is 92% and 112% higher than the SISO system, respectively.

Abstract Among today’s nonvolatile memories, ferroelectric-based capacitors, tunnel junctions and field-effect transistors (FET) are already industrially integrated and/or intensively investigated to improve their performances. Concurrently, because of the tremendous development of artificial intelligence and big-data issues, there is an urgent need to realize high-density crossbar arrays, a prerequisite for the future of memories and emerging computing algorithms. Here, a two-terminal ferroelectric fin diode (FFD) in which a ferroelectric capacitor and a fin-like semiconductor channel are combined to share both top and bottom electrodes is designed. Such a device not only shows both digital and analog memory functionalities but is also robust and universal as it works using two very different ferroelectric materials. When compared to all current nonvolatile memories, it cumulatively demonstrates an endurance up to 1010 cycles, an ON/OFF ratio of ~102, a feature size of 30 nm, an operating energy of ~20 fJ and an operation speed of 100 ns. Beyond these superior performances, the simple two-terminal structure and their self-rectifying ratio of ~ 104 permit to consider them as new electronic building blocks for designing passive crossbar arrays which are crucial for the future in-memory computing.

This paper aims to establish a more standardized and regulated carbon emission accounting model for sponge cities by unifying the accounting content for carbon emissions and clarifying the relationships between carbon reduction benefits, carbon reduction effects, and carbon sequestration, in order to evaluate the carbon reduction outcomes and mechanisms of sponge city construction. Based on a Life Cycle Assessment (LCA) carbon emission accounting model using the carbon emission factor method, a newly constructed residential area in Tianshui City, Gansu Province, was selected as a case study, and the carbon emission reduction effect of sponge city construction was then investigated. Results indicated that the 30-year full life cycle carbon emissions for sponge city construction in the newly constructed residential area amounted to 828.98 tons, compared to 744.28 tons of CO2 reduction in traditional construction, representing a 47.31% reduction in carbon emissions. Over a 30-year life cycle, this equated to a total carbon emission reduction effect of 1460.31 tons. Additionally, under various rainfall scenarios in a typical year, the carbon emission reduction effect of sponge city construction exceeded the carbon emissions, achieving carbon neutrality within 22 to 30 years of operation. This demonstrates that the carbon emission reduction effect of sponge city communities is significant. The findings of this study provide data and a theoretical basis for the low-carbon construction of sponge cities in China.

Abstract Background The aim of this study was to evaluate the precision and feasibility of patient-specific instruments (PSI) in total hip arthroplasty (THA) as compared to the traditional free-hand (FRH) approach. Methods During the period of January 1, 2021 to December 31, 2022, a randomized allocation was used for patients receiving unilateral primary THA to either the PSI or conventional operation group. The placement and size of the PSI were specifically chosen to guide femoral neck resection and prosthesis implantation. The study analyzed component positions and evaluated radiographic and clinical outcomes in 30 patients who received PSI-assisted THAs and 30 patients who received FRH THAs. This study was registered at China Clinical Trial Registry (number: ChiCTR2300072325) on June 9th, 2023. Results The use of PSI in THA resulted in significantly higher precision in achieving the desired component position as compared to the FRH approach. The PSI group showed significantly smaller absolute errors of femoral anteversion (p

Prostate cancer (PCa) remains a leading cause of mortality among American men, with metastatic and recurrent disease posing significant therapeutic challenges due to a limited comprehension of the underlying biological processes governing disease initiation, dormancy, and progression. The conventional use of PCa cell lines has proven inadequate in elucidating the intricate molecular mechanisms driving PCa carcinogenesis, hindering the development of effective treatments. To address this gap, patient-derived primary cell cultures have been developed and play a pivotal role in unraveling the pathophysiological intricacies unique to PCa in each individual, offering valuable insights for translational research. This review explores the applications of the conditional reprogramming (CR) cell culture approach, showcasing its capability to rapidly and effectively cultivate patient-derived normal and tumor cells. The CR strategy facilitates the acquisition of stem cell properties by primary cells, precisely recapitulating the human pathophysiology of PCa. This nuanced understanding enables the identification of novel therapeutics. Specifically, our discussion encompasses the utility of CR cells in elucidating PCa initiation and progression, unraveling the molecular pathogenesis of metastatic PCa, addressing health disparities, and advancing personalized medicine. Coupled with the tumor organoid approach and patient-derived xenografts (PDXs), CR cells present a promising avenue for comprehending cancer biology, exploring new treatment modalities, and advancing precision medicine in the context of PCa. These approaches have been used for two NCI initiatives (PDMR: patient-derived model repositories; HCMI: human cancer models initiatives).

Abstract Breast cancer is the most common malignant tumor and the leading cause of cancer‐related deaths in women worldwide. Effective means of predicting the prognosis of breast cancer are very helpful in guiding treatment and improving patients' survival. Features extracted by radiomics reflect the genetic and molecular characteristics of a tumor and are related to its biological behavior and the patient's prognosis. Thus, radiomics provides a new approach to noninvasive assessment of breast cancer prognosis. Ultrasound is one of the commonest clinical means of examining breast cancer. In recent years, some results of research into ultrasound radiomics for diagnosing breast cancer, predicting lymph node status, treatment response, recurrence and survival times, and other aspects, have been published. In this article, we review the current research status and technical challenges of ultrasound radiomics for predicting breast cancer prognosis. We aim to provide a reference for radiomics researchers, promote the development of ultrasound radiomics, and advance its clinical application.

Abstract Approximately 20% of aged captive giant pandas (Ailuropoda melanoleuca) have cataracts that impair their quality of life. To identify potential biomarkers of cataract formation, we carried out a quantitative proteomics analysis of 10 giant pandas to find proteins differing in abundance between healthy and cataract-bearing animals. We identified almost 150 proteins exceeding our threshold for differential abundance, most of which were associated with GO categories related to extracellular localization. The most significant differential abundance was associated with components of the proteasome and other proteins with a role in proteolysis or its regulation, most of which were depleted in pandas with cataracts. Other modulated proteins included components of the extracellular matrix or cytoskeleton, as well as associated signaling proteins and regulators, but we did not find any differentially expressed transcription factors. These results indicate that the formation of cataracts involves a complex post-transcriptional network of signaling inside and outside lens cells to drive stress responses as a means to address the accumulation of protein aggregates triggered by oxidative damage. The modulated proteins also indicate that it should be possible to predict the onset of cataracts in captive pandas by taking blood samples and testing them for the presence or absence of specific protein markers.

Abstract Lung cancer, with non‐small cell lung cancer (NSCLC) being the main subtype, is the leading cause of cancer death worldwide, which is mainly due to the cancer metastasis. Glutathione peroxidase 2 (GPX2), an antioxidant enzyme, is involved in tumor progression and metastasis. Nevertheless, the role of GPX2 in NSCLC metastasis has not been clarified. In this study, we found that GPX2 expression was elevated in NSCLC tissues and high GPX2 expression was correlated with poor prognosis in patients with NSCLC. In addtion, GPX2 expression was related to the patient's clinicopathological features, including lymph node metastasis, tumor size, and TNM stage. Overexpression of GPX2 promoted epithelial–mesenchymal transition (EMT), migration, and invasion of NSCLC cells in vitro. Knockdown of GPX2 showed the opposite effects in vitro and inhibited the metastasis of NSCLC cells in nude mice. Furthermore, GPX2 reduced reactive oxygen species (ROS) accumulation and activated the PI3K/AKT/mTOR/Snail signaling axis. Therefore, our results indicate that GPX2 promotes EMT and metastasis of NSCLC cells by activating the PI3K/AKT/mTOR/Snail signaling axis via the removal of ROS. GPX2 may be an effective diagnostic and prognostic biomarker for NSCLC.

The Chang 9 oil layer deposits within Ansai District, Ordos Basin, yield considerable reserves of crude oil, yet their source remains ambiguous. This research endeavor was designed to characterize the Chang 9 crude oil and the Chang 7 and Chang 9 source rocks (SRs) of the Yan-Chang Formation via organic geochemical analysis. The results indicate that the Chang 9 crude oil exhibits a Pr/Ph ratio of 0.84–2.29 and Ga/C30H less than 0.1, implying formed in a weak reduction to weak oxidation freshwater environment. The regular sterane C27-C28-C29 configuration assumes an inversed “L” type, reflecting mixed sources and dominant terrestrial plant input. Ratios such as C2920S/20S+20R (0.54–0.6) and C29ββ/ββ+αα (0.44–0.58) indicate a mature oil stage. The depositional environment of the C7 and C9 SRs is similar, with weak oxidation to reduction conditions, and consists mainly of Type I and II organics, with a relatively higher maturity of the C9 SRs. A difference in C19/C23TT and C30D/C30H was found between the C7 and C9 SRs. The results show that the C9 crude oils have a similar C19/C23TT with the C9 SRs and similar diahopanes distribution with Class II SRs (C7 and part of the C9 SRs). Thus, the C9 crude oils most likely originate from the C9 SR mixed with the C7 SRs.

Analog memory presents a promising solution in the face of the growing demand for energy-efficient artificial intelligence (AI) at the edge. In this study, we demonstrate efficient deep neural network transfer learning utilizing hardware and algorithm co-optimization in an analog resistive random-access memory (ReRAM) array. For the first time, we illustrate that in open-loop deep neural network (DNN) transfer learning for image classification tasks, convergence rates can be accelerated by approximately 3.5 times through the utilization of co-optimized analog ReRAM hardware and the hardware-aware Tiki-Taka v2 (TTv2) algorithm. A simulation based on statistical 14 nm CMOS ReRAM array data provides insights into the performance of transfer learning on larger network workloads, exhibiting notable improvement over conventional training with random initialization. This study shows that analog DNN transfer learning using an optimized ReRAM array can achieve faster convergence with a smaller dataset compared to training from scratch, thus augmenting AI capability at the edge.

To solve the problem of low interfacial bonding strength caused by the violent reaction of the titanium/stainless steel interface, the corrugated rolling-flat rolling (CFR) process was used to introduce inhomogeneous plastic deformation, and the titanium/stainless steel was prepared. The interface morphology and strain distribution characteristics of flat rolling (FR) and CFR titanium/stainless steel were studied in comparison. The effect of the inhomogeneous plastic deformation on interfacial microstructure and properties was investigated, and the intrinsic mechanism was revealed. The results show that FR titanium/stainless steel interface is relatively flat and exists in a large number of continuous intermetallic compounds. The interfacial bonding strength is at a low level. In CFR titanium/stainless steel, the interface shows a wave-shape and has few intermetallic compounds. The interfacial bonding strength of the peak, waist and trough are all above 240 MPa. The continuous intermetallic compounds of FR titanium/stainless steel split the interface, leading to low interfacial bonding strength. In the CFR process, the strong inhomogeneous plastic deformation effect reduces the generation of continuous intermetallic compounds at the interface. Meanwhile, the increase of deformation storage energy improves the interfacial metallurgical bonding effect. In combination with the effect of a larger interfacial contact area, a high level of interfacial bonding strength is achieved. The CFR process is an effective way to prepare titanium/stainless steel with excellent interfacial bonding strength.

Abstract Cellular senescence provides a protective barrier against tumorigenesis in precancerous or normal tissues upon distinct stressors. However, the detailed mechanisms by which tumor cells evade premature senescence to malignant progression remain largely elusive. Here we reported that RBM4 adversely impacted cellular senescence to favor glutamine-dependent survival of esophageal squamous cell carcinoma (ESCC) cells by dictating the activity of LKB1, a critical governor of cancer metabolism. The level of RBM4 was specifically elevated in ESCC compared to normal tissues, and RBM4 overexpression promoted the malignant phenotype. RBM4 contributed to overcome H-RAS- or doxorubicin-induced senescence, while its depletion caused P27-dependent senescence and proliferation arrest by activating LKB1-AMPK-mTOR cascade. Mechanistically, RBM4 competitively bound LKB1 to disrupt the LKB1/STRAD/MO25 heterotrimeric complex, subsequently recruiting the E3 ligase TRIM26 to LKB1, promoting LKB1 ubiquitination and degradation in nucleus. Therefore, such molecular process leads to bypassing senescence and sustaining cell proliferation through the activation of glutamine metabolism. Clinically, the ESCC patients with high RBM4 and low LKB1 have significantly worse overall survival than those with low RBM4 and high LKB1. The RBM4 high/LKB1 low expression confers increased sensitivity of ESCC cells to glutaminase inhibitor CB-839, providing a novel insight into mechanisms underlying the glutamine-dependency to improve the efficacy of glutamine inhibitors in ESCC therapeutics.

Abstract Bladder cancer (BC) is a clinical challenge worldwide with late clinical presentation, poor prognosis, and low survival rates. Traditional cystoscopy and tissue biopsy are routine methods for the diagnosis, prognosis, and monitoring of BC. However, due to the heterogeneity and limitations of tumors, such as aggressiveness, high cost, and limited applicability of longitudinal surveillance, the identification of tumor markers has attracted significant attention in BC. Over the past decade, liquid biopsies (e.g., blood) have proven to be highly efficient methods for the discovery of BC biomarkers. This noninvasive sampling method is used to analyze unique tumor components released into the peripheral circulation and allows serial sampling and longitudinal monitoring of tumor progression. Several liquid biopsy biomarkers are being extensively studied and have shown promising results in clinical applications of BC, including early detection, detection of microscopic residual disease, prediction of recurrence, and response to therapy. Therefore, in this review, we aim to provide an update on various novel blood-based liquid biopsy markers and review the advantages and current limitations of liquid biopsy in BC therapy. The role of blood-based circulating tumor cells, circulating tumor DNA, cell-free RNA, exosomes, metabolomics, and proteomics in diagnosis, prognosis, and treatment monitoring, and their applicability to the personalized management of BC, are highlighted.

Carbon nanotube (CNT)-based networks are promising reinforcements for polymer nanocomposites without the issue of CNT agglomeration. In this study, the CNT junction, a vital and representative structure of CNT-based networks, was applied as the reinforcement of the polyethylene (PE) matrix. The tensile properties of the CNT-junction/PE nanocomposite were investigated via molecular dynamics (MD) simulations and compared with those of pure PE matrix and conventional CNT/PE nanocomposites. The CNT junction was found to significantly increase the mechanical properties of the PE matrix. The Young’s modulus, yield strength, and toughness rose by 500%, 100%, and 200%, respectively. This mechanism is related to the enhanced interfacial energy, which makes the polymer matrix denser and stimulates the bond and angle deformations of the polymer chains. Furthermore, the CNT junction demonstrated a more profitable reinforcement efficiency compared to conventional straight CNTs in the PE matrix. Compared to the ordinary CNT/PE model, the improvements in the Young’s modulus and toughness induced by the CNT junction were up to 60% and 25%. This is attributed to the reduced mobility induced by the geometry of the CNT junction and stronger interfacial interactions provided by the Stone–Wales defects of the CNT junction, slowing down the void propagation of the nanocomposite. With the understanding of the beneficial reinforcing effect of the CNT junction, this study provides valuable insights for the design and application of CNT-based networks in polymer nanocomposites.

Summary: Background: The causes for immune-mediated inflammatory diseases (IMIDs) are diverse and the incidence trends of IMIDs from specific causes are rarely studied. The study aims to investigate the pattern and trend of IMIDs from 1990 to 2019. Methods: We collected detailed information on six major causes of IMIDs, including asthma, inflammatory bowel disease, multiple sclerosis, rheumatoid arthritis, psoriasis, and atopic dermatitis, between 1990 and 2019, derived from the Global Burden of Disease study in 2019. The average annual percent change (AAPC) in number of incidents and age standardized incidence rate (ASR) on IMIDs, by sex, age, region, and causes, were calculated to quantify the temporal trends. Findings: In 2019, rheumatoid arthritis, atopic dermatitis, asthma, multiple sclerosis, psoriasis, inflammatory bowel disease accounted 1.59%, 36.17%, 54.71%, 0.09%, 6.84%, 0.60% of overall new IMIDs cases, respectively. The ASR of IMIDs showed substantial regional and global variation with the highest in High SDI region, High-income North America, and United States of America. Throughout human lifespan, the age distribution of incident cases from six IMIDs was quite different. Globally, incident cases of IMIDs increased with an AAPC of 0.68 and the ASR decreased with an AAPC of −0.34 from 1990 to 2019. The incident cases increased across six IMIDs, the ASR of rheumatoid arthritis increased (0.21, 95% CI 0.18, 0.25), while the ASR of asthma (AAPC = −0.41), inflammatory bowel disease (AAPC = −0.72), multiple sclerosis (AAPC = −0.26), psoriasis (AAPC = −0.77), and atopic dermatitis (AAPC = −0.15) decreased. The ASR of overall and six individual IMID increased with SDI at regional and global level. Countries with higher ASR in 1990 experienced a more rapid decrease in ASR. Interpretation: The incidence patterns of IMIDs varied considerably across the world. Innovative prevention and integrative management strategy are urgently needed to mitigate the increasing ASR of rheumatoid arthritis and upsurging new cases of other five IMIDs, respectively. Funding: The Global Burden of Disease Study is funded by the Bill and Melinda Gates Foundation. The project funded by Scientific Research Fund of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital (2022QN38).

Abstract Protein-ligand docking is a computational method for identifying drug leads. The method is capable of narrowing a vast library of compounds down to a tractable size for downstream simulation or experimental testing and is widely used in drug discovery. While there has been progress in accelerating scoring of compounds with artificial intelligence, few works have bridged these successes back to the virtual screening community in terms of utility and forward-looking development. We demonstrate the power of high-speed ML models by scoring 1 billion molecules in under a day (50 k predictions per GPU seconds). We showcase a workflow for docking utilizing surrogate AI-based models as a pre-filter to a standard docking workflow. Our workflow is ten times faster at screening a library of compounds than the standard technique, with an error rate less than 0.01% of detecting the underlying best scoring 0.1% of compounds. Our analysis of the speedup explains that another order of magnitude speedup must come from model accuracy rather than computing speed. In order to drive another order of magnitude of acceleration, we share a benchmark dataset consisting of 200 million 3D complex structures and 2D structure scores across a consistent set of 13 million “in-stock” molecules over 15 receptors, or binding sites, across the SARS-CoV-2 proteome. We believe this is strong evidence for the community to begin focusing on improving the accuracy of surrogate models to improve the ability to screen massive compound libraries 100 × or even 1000 × faster than current techniques and reduce missing top hits. The technique outlined aims to be a fast drop-in replacement for docking for screening billion-scale molecular libraries.

Abstract Background Human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) is still among the leading causes of disease burden and mortality in sub-Saharan Africa (SSA), and the world is not on track to meet targets set for ending the epidemic by the Joint United Nations Programme on HIV/AIDS (UNAIDS) and the United Nations Sustainable Development Goals (SDGs). Precise HIV burden information is critical for effective geographic and epidemiological targeting of prevention and treatment interventions. Age- and sex-specific HIV prevalence estimates are widely available at the national level, and region-wide local estimates were recently published for adults overall. We add further dimensionality to previous analyses by estimating HIV prevalence at local scales, stratified into sex-specific 5-year age groups for adults ages 15–59 years across SSA. Methods We analyzed data from 91 seroprevalence surveys and sentinel surveillance among antenatal care clinic (ANC) attendees using model-based geostatistical methods to produce estimates of HIV prevalence across 43 countries in SSA, from years 2000 to 2018, at a 5 × 5-km resolution and presented among second administrative level (typically districts or counties) units. Results We found substantial variation in HIV prevalence across localities, ages, and sexes that have been masked in earlier analyses. Within-country variation in prevalence in 2018 was a median 3.5 times greater across ages and sexes, compared to for all adults combined. We note large within-district prevalence differences between age groups: for men, 50% of districts displayed at least a 14-fold difference between age groups with the highest and lowest prevalence, and at least a 9-fold difference for women. Prevalence trends also varied over time; between 2000 and 2018, 70% of all districts saw a reduction in prevalence greater than five percentage points in at least one sex and age group. Meanwhile, over 30% of all districts saw at least a five percentage point prevalence increase in one or more sex and age group. Conclusions As the HIV epidemic persists and evolves in SSA, geographic and demographic shifts in prevention and treatment efforts are necessary. These estimates offer epidemiologically informative detail to better guide more targeted interventions, vital for combating HIV in SSA.

The mechanical incompatibilities between ferrite and martensite at the cladding interface of stainless steel (SS)/carbon steel (CS) clad plates can result in stress concentration and interface cracks. In this paper, 304 SS/Q235 CS clad plates were prepared by liquid-solid (L-S) composite casting, and the mechanical incompatibilities between ferrite and martensite reduced by constructing gradient carbides in the interfacial ferrite. The precipitation behavior of the gradient carbides was analyzed, and the strengthening mechanism was revealed. The ultimate strength of the SS/CS clad plates was 370 MPa when stretched perpendicular to the cladding interface, and the SS/CS clad plates fractured in the CS that was far from the cladding interface. The interfacial microstructures from the CS to the SS were ferrite, M7C3 carbides, and lath martensite, and the carbides content gradually decreased toward the CS. During the L-S composite process, a micro-melting region with decreased volume fraction of interdendritic liquid to the CS formed at the cladding interface. The C, Cr, and Ni mixed and diffused in the interdendritic liquid, and the gradient distribution of elements resulted in the precipitation of coherent M7C3 carbides whose volume fraction decreased toward the CS. The coherent strengthening and precipitation strengthening of carbides strengthened the interfacial ferrite and resulted in a gradient strengthening, which reduced the mechanical incompatibilities between ferrite and martensite at the cladding interface. Additionally, the gradient carbides changed the stress state at the cladding interface and improved the interfacial bonding strength.

Objective: This study aimed to investigate the effect of whole-body vibration training (WBVT) combined with KAATSU training (KT) on lower limb joint muscle strength and to provide a reference for improving muscle strength in older women.Methods: A total of 86 healthy older people was randomly divided into WBVT group (WG, n = 21), KT group (KG, n = 22), combined intervention group (CIG, n = 20) and control group (CG, n = 23). WG and CIG subjects underwent WBVT, and KG and CIG subjects underwent 150 mmHg and lower limb joint and local compression intervention for 16 weeks (three times per week, about 15 min/time). The peak torque (PT) and endurance ratio (ER) of joint flexion or extension were tested for all subjects.Results: 1) Results at 16 weeks were compared with the baseline data. The knee extension and ankle flexion PT (60°/s) in CIG increased by 14.3% and 15.3%, respectively (p < 0.05). The knee extension PT (180°/s) increased by 16.9, 18.4% and 33.3% in WG, KG and CIG (p < 0.05), respectively, and the ankle extension PT (180°/s) in CIG increased by 31.1% (p < 0.05). The hip, knee extension and ankle flexion ER increased by 10.0, 10.9% and 5.7% in CIG (p < 0.05), respectively. 2) Results were compared among groups at 16 weeks. The relative changes were significantly lower in WG, KG and CG compared to CIG in the knee extension and ankle flexion PT (60°/s) (p < 0.05). The relative changes were significantly greater in WG, KG and CIG compared to CG in the knee extension PT (180°/s) (p < 0.05). The relative changes were significantly lower in WG, KG and CG compared to CIG in the ankle extension PT (180°/s) (p < 0.05). The relative changes were significantly lower in WG, KG and CG compared to CIG in the hip extension ER (p < 0.05). The relative changes were significantly lower in CG compared to CIG in the knee extension ER (p < 0.05).Conclusion: Sixteen-week WBVT and KT increased the knee extensor strength in older women. Compared with a single intervention, the combined intervention had better improvements in the knee extensor and ankle flexor and extensor strength and hip extension muscle endurance. Appears to be some additional benefit from combined intervention above those derived from single-interventions.

Most photoacoustic computed tomography (PACT) systems usually ignore the anisotropy of the tissue absorption coefficient, which will lead to the lack of information in reconstructed images. In this work, the effect is addressed of the possible optical absorption anisotropy of tissue on PACT images. The functional relationship is derived between the photoacoustic response and the polarization angle of the excitation light. An adaptive polarized light photoacoustic imaging (AP-PACT) approach is proposed and shown to make up for the lack of imaging information and achieve optimal image contrast when imaging samples with anisotropic optical absorption, by utilizing the standard deviation of photoacoustic response as the feedback signal in an adaptive data acquisition process. The method is implemented both on phantom and in vitro experiments, which show that AP-PACT can recover anisotropic absorption-related information from reconstructed images and thus significantly improve their quality.

The complex and variable oceanic environment challenges channel modeling of Underwater Wireless Optical Communication (UWOC) systems. Most of the classical modeling methods focus mainly on the water environment and ignore the effect of communication equipment on signal transmission, thus making it difficult to model the UWOC channel’s complicated characteristics comprehensively. In this work, a UWOC channel emulator based on Deep Convolutional Conditional Generative Adversarial Networks is established and verified to address the challenge, which can effectively learn the characteristics of channel response and generate emulated signals with randomness like a real UWOC system in a practical application environment. Compared with the approaches based on multi-layer perceptron and convolutional neural network, the experimental results of the proposed method indicate outstanding performances in time domain, frequency domain and universality with different turbidity levels, respectively. This approach provides a new idea for applying deep learning techniques to the field of UWOC channel modeling.

Abstract Analog storage through synaptic weights using conductance in resistive neuromorphic systems and devices inevitably generates harmful heat dissipation. This thermal issue not only limits the energy efficiency but also hampers the very‐large‐scale and highly complicated hardware integration as in the human brain. Here we demonstrate that the synaptic weights can be simulated by reconfigurable non‐volatile capacitances of a ferroelectric‐based memcapacitor with ultralow‐power consumption. The as‐designed metal/ferroelectric/metal/insulator/semiconductor memcapacitor shows distinct 3‐bit capacitance states controlled by the ferroelectric domain dynamics. These robust memcapacitive states exhibit uniform maintenance of more than 104 s and well endurance of 109 cycles. In a wired memcapacitor crossbar network hardware, analog vector‐matrix multiplication is successfully implemented to classify 9‐pixel images by collecting the sum of displacement currents (I = C × dV/dt) in each column, which intrinsically consumes zero energy in memcapacitors themselves. Our work sheds light on an ultralow‐power neural hardware based on ferroelectric memcapacitors.

A high-performance resonant metasurface is rather promising for diverse application areas such as optical sensing and filtering. Herein, a metal–insulator–metal (MIM) optical sensor with merits of a high quality-factor (Q-factor), multiple operating bands, and high spectrum contrast is proposed using plasmonic square bracket dimer metasurface. Due to the complex square bracket itself, a dimer structure of two oppositely placed square brackets, and metasurface array configuration, multiple kinds of mode coupling can be devised in the inner and outer elements within the metasurface, enabling four sensing channels with the sensitivities higher than 200 nm/RIU for refractive index sensing. Among them, the special sensing channel based on the reflection-type surface lattice resonance (SLR) mechanism has a full width at half maximum (FWHM) of only 2 nm, a high peak-to-dip signal contrast of 0.82, a high Q-factor of 548, and it can also behave as a good sensing channel for the thickness measurement of the deposition layer. The multi-band sensor can work normally in a large refractive index or thickness range, and the number of resonant channels can be further increased by simply breaking the structural symmetry or changing the polarization angle of incident light. Equipped with unique advantages, the suggested plasmonic metasurface has great potential in sensing, monitoring, filtering, and other applications.

To investigate the quantitative relationship between the volume capture of rainfall and carbon emissions from bioretention facilities, this study introduces the concept of the carbon intensity of volume capture of rainfall. The influence of four key factors—climatic conditions, aquifer height, permeability coefficient, and facility area—was investigated using a residential neighborhood in Tianshui, China, as an example. The results reveal that the carbon intensity value is influenced not only by external environmental changes but also by the inherent attributes of bioretention facilities, such as aquifer height, permeability coefficient, and facility area. The maximum carbon intensity value for the volume capture of rainfall was −0.0005 kg CO2/m3, while the minimum was −0.0852 kg CO2/m3, representing a substantial difference of approximately 169 times. Orthogonal experiments identified the facility area as the most significant influencing factor on carbon intensity, with a correlation coefficient of 0.0520. The area of bioretention facilities can be prioritized to meet deployment requirements, taking into account volume capture reduction effects and carbon emissions. For facilities with a high carbon intensity, an emphasis should be placed on enhancing carbon reduction benefits, and various initiatives can be implemented to achieve this goal.

Carbon nanotube (CNT)-based networks have wide applications, in which structural design and control are important to achieve the desired performance. This paper focuses on the mechanism behind the structure-dependent mechanical performance of a CNT-based hierarchical network, named a super carbon nanotube (SCNT), which can provide valuable guidance for the structural design of CNT-based networks. Through molecular dynamic (MD) simulations, the mechanical properties of the SCNTs were found to be affected by the arrangement, length and chirality of the CNTs. Different CNT arrangements cause variations of up to 15% in the ultimate tensile strains of the SCNTs. The CNT length determines the tangent elastic modulus of the SCNTs at the early stage. Changing the CNT chirality could transform the fracture modes of the SCNT from brittle to ductile. The underlying mechanisms were found to be associated with the deformation mode of the SCNTs. All the SCNTs undergo a top-down hierarchical deformation process from the network-level angle variations to the CNT-level elongations, but some vital details vary, such as the geometrical parameters. The CNT arrangement induces different deformation contributors of the SCNTs. The CNT length affects the beginning point of the CNT elongation deformation. The CNT chirality plays a crucial role in the stability of the junction’s atomic topology, where the crack propagation commences.

Abstract For the linear Lagrange interpolation over a triangular domain, we propose an efficient algorithm to rigorously evaluate the interpolation error constant under the maximum norm by using the finite-element method (FEM). In solving the optimization problem corresponding to the interpolation error constant, the maximum norm in the constraint condition is the most difficult part to process. To handle this difficulty, a novel method is proposed by combining the orthogonality of the space decomposition using the Fujino–Morley FEM space and the convex-hull property of the Bernstein representation of functions in the FEM space. Numerical results for the lower and upper bounds of the interpolation error constant for triangles of various types are presented to verify the efficiency of the proposed method.

Abstract Background CDK4/6 inhibitors combined with endocrine therapy has become the preferred treatment approach for patients with estrogen receptor-positive metastatic breast cancer. However, the predictive biomarkers and mechanisms of innate resistance to CDK4/6 inhibitors remain largely unknown. We sought to elucidate the molecular hallmarks and therapeutically actionable features of patients with resistance to CDK4/6 inhibitors. Methods A total of 36 patients received palbociclib and endocrine therapy were included in this study as the discovery cohort. Next-generation sequencing of circulating tumour DNA in these patients was performed to evaluate somatic alterations associated with innate resistance to palbociclib. Then the candidate biomarker was validated in another independent cohort of 104 patients and publicly available datasets. The resistance was verified in parental MCF-7 and T47D cells, as well as their derivatives with small interfering RNA transfection and lentivirus infection. The relevant mechanism was examined by RNA sequencing, chromatin immunoprecipitation and luciferase assay. Patient-derived organoid and patient-derived xenografts studies were utilized to evaluated the antitumor activity of rational combinations. Results In the discovery cohort, S6K1 amplification (3/35, 9%) was identified as an important reason for innate resistance to CDK4/6 inhibitors. In the independent cohort, S6K1 was overexpressed in 15/104 (14%) patients. In those who had received palbociclib treatment, patients with high-expressed S6K1 had significantly worse progression free survival than those with low S6K1 expression (hazard ratio = 3.0, P = 0.0072). Meta-analysis of public data revealed that patients with S6K1 amplification accounted for 12% of breast cancers. Breast cancer patients with high S6K1 expression had significantly worse relapse-free survival (hazard ratio = 1.31, P

Abstract Pine wilt disease (PWD) is a worldwide forest disease caused by pine wood nematode (PWN). In this article, we investigated the composition, organization, correlation, and function of the endophytic microbial community in Pinus massoniana field with and without PWN. Samples were taken from branches, upper, middle, and lower trunks, as well as soil, from both healthy and infected trees. The results showed that the fungal diversity of healthy pines is around 1.1 times that of infected pines, while the bacterial diversity is about 0.75 times that of infected pines at the OTUs level. An increase of the abundance of pathogenic fungus such as Saitozyma, Graphilbum, Diplodia, Candida, Pseudoxanthomonas, Dyella and Pantoea was witnessed in infected pines according to the result of LEfSe. Furthermore, Ophiostoma and saprophytic fungus such as Entomocorticium, ganoderma, tomentella, entomocorticium were exclusively prominent in infected pines, which were substantially and highly connected with other species (p

ObjectivesThis study aimed to explore the value of conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) radiomics to diagnose breast cancer and predict its molecular subtype.MethodA total of 170 lesions (121 malignant, 49 benign) were selected from March 2019 to January 2022. Malignant lesions were further divided into six categories of molecular subtype: (non-)Luminal A, (non-)Luminal B, (non-)human epidermal growth factor receptor 2 (HER2) overexpression, (non-)triple-negative breast cancer (TNBC), hormone receptor (HR) positivity/negativity, and HER2 positivity/negativity. Participants were examined using CUS and CEUS before surgery. Regions of interest images were manually segmented. The pyradiomics toolkit and the maximum relevance minimum redundancy algorithm were utilized to extract and select features, multivariate logistic regression models of CUS, CEUS, and CUS combined with CEUS radiomics were then constructed and evaluated by fivefold cross-validation.ResultsThe accuracy of the CUS combined with CEUS model was superior to CUS model (85.4% vs. 81.3%, p

Interfacial performance of stainless steel/carbon steel (SS/CS) laminated composite is crucial for further manufacturing and application. Here, we reported a new strategy for fabricating the SS/CS laminated composites that composed of heterogeneous lamella structure at the cladding interface zone, by employing liquid–solid bonding and subsequent hot rolling. Different rolling temperatures were applied for comparison of the formation of heterogeneous lamella structure and their influences on the mechanical properties of the cladding interface, and the mechanisms of enhanced interfacial shear strength and ductility by the heterogenous lamella structure were discussed. A metallurgical bonding interface with intensive elements diffusion was obtained by liquid–solid bonding method, and coarse equiaxed grains and a wider decarburized layer formed at the cladding interface zone. Under rolling temperature of 900 °C, the mechanical incompatibilities of cladding interface zone and lower temperature resulted in heterodeformation and inefficient driving force of recrystallization, resulting in a heterogenous lamella structure consisted of hardened austenite region, coarse-grained ferrite region and fine-grained pearlite and ferrite region at the cladding interface zone of SS/CS laminated composite, which obviously improved the interfacial shear strength and ductility of the SS/CS laminated composites due to back stress strengthening and hardening.

Abstract Biology and transcriptomes of non-cancerous human mammary epithelial cells at risk for breast cancer development were explored following primary isolation utilizing conditional reprogramming cell technology from mastectomy tissue ipsilateral to invasive breast cancer. Cultures demonstrated consistent categorizable behaviors. Relative viability and mammosphere formation differed between samples but were stable across three different mammary-specific media. E2F cell cycle target genes expression levels were positively correlated with viability and advancing age was inversely associated. Estrogen growth response was associated with Tissue necrosis factor signaling and Interferon alpha response gene enrichment. Neoadjuvant chemotherapy exposure significantly altered transcriptomes, shifting them towards expression of genes linked to mammary stem cell formation. Breast cancer prognostic signature sets include genes that in normal development are limited to specific stages of pregnancy or the menstrual cycle. Sample transcriptomes were queried for stage specific gene expression patterns. All cancer samples and a portion of high-risk samples showed overlapping stages reflective of abnormal gene expression patterns, while other high-risk samples exhibited more stage specific patterns. In conclusion, at-risk cells preserve behavioral and transcriptome diversity that could reflect different risk profiles. It is possible that prognostic platforms analogous to those used for breast cancer could be developed for high-risk mammary cells.

Abstract Background Oral squamous cell carcinoma (OSCC) is one of the common cancers worldwide. The lack of specific biomarkers and therapeutic targets leads to delayed diagnosis and hence the poor prognosis of OSCC patients. Thus, it is urgent to identify effective biomarkers and therapeutic targets for OSCC. Methods We established the golden hamster carcinogenic model of OSCC induced by 7,12-dimethylbenz(a) anthrancene (DMBA) and used mRNA microarrays to detect the differentially expressed genes (DEGs). DEGs were validated in OSCC clinical tissue microarrays using immunohistochemistry method. Whole transcriptome sequencing was performed to obtain an overview of biological functions of Lsm12. PCR assay and sequencing were employed to investigate the alternative splicing of genes regulated by Lsm12. Cell proliferation, colony formation, Transwell migration and invasion assay and in vivo tumor formation assay were performed to investigate the roles of Lsm12 and two transcript variants of USO1 in OSCC cells. Results Lsm12 was identified to be significantly up-regulated in the animal model of OSCC tumorigenesis, which was validated in the clinical OSCC samples. In the paired normal tissues, Lsm12 staining was negative (91%, 92/101) or weak, while in OSCC tissues, positive rate is 100% and strong staining spread over the whole tissues in 93 (93/101, 92%) cases. Lsm12 overexpression significantly promoted OSCC cell growth, colony formation, migration and invasion abilities, while Lsm12 knockdown showed the opposite trends on these phenotypes and obviously inhibited the tumor formation in vivo. Furthermore, Lsm12 overexpression caused the inclusion of USO1 exon 15 and Lsm12 knockdown induced exon 15 skipping. Exon 15-retained USO1 significantly promoted the malignant phenotypes of OSCC cells when compared with the exon 15-deleted USO1. Conclusions We identified Lsm12, a novel tumorigenesis-related gene, as an important regulator involved in OSCC tumorigenesis. Lsm12 is a novel RNA-splicing related gene and can regulate the alternative splicing of USO1 exon 15 which was associated closely with OSCC carcinogenesis. Our findings thus provide that Lsm12 might be a potent biomarker and potential therapeutic target for OSCC.

Abstract Bladder cancer (BC) is one of the most common malignant tumors of the urinary system, and cisplatin (CDDP) is a critical chemical drug for the treatment of BC. However, CDDP-resistance seriously limits the therapeutic efficacy of this drug for clinical utilization. Thus, identification of pivotal molecule targets that regulate CDDP-resistance in BC become urgent and necessary. In this study, we firstly identified a novel BC-associated circular RNA circ_0058063 that participates in the regulation of CDDP-resistance in BC. Specifically, circ_0058063 was significantly overexpressed in CDDP-resistant tissue and cells, in contrast with the corresponding CDDP-sensitive counterparts. Further loss-of-function experiments validated that downregulation of circ_0058063 suppressed cell proliferation and tumor growth, whereas induced cell apoptosis in the CDDP-resistant BC cells in vitro and in vivo. In addition, we disclosed that circ_0058063 acts as a sponge for miR-335-5p to positively regulate B2M expression, and further rescuing experiments verified that the enhancing effects of sh-circ_0058063 on CDDP-sensitivity in the CDDP-resistant BC cells were abrogated by silencing miR-335-5p. Taken together, our results demonstrated that circ_0058063 contributed to CDDP resistance of bladder cancer cells via sponging miR-335-5p, and B2M might be the downstream effector gene. This study firstly evidenced that targeting circ_0058063 might be an effective strategy to improve CDDP-sensitivity in BC.

The cocktail party problem can be more effectively addressed by leveraging the speaker’s visual and audio information. This paper proposes a method to improve the audio’s separation using two visual cues: facial features and lip movement. Firstly, residual connections are introduced in the audio separation module to extract detailed features. Secondly, considering the video stream contains information other than the face, which has a minimal correlation with the audio, an attention mechanism is employed in the face module to focus on crucial information. Then, the loss function considers the audio-visual similarity to take advantage of the relationship between audio and visual completely. Experimental results on the public VoxCeleb2 dataset show that the proposed model significantly enhanced SDR, PSEQ, and STOI, especially 4 dB improvements in SDR.

Preclinical in vitro models play an important role in studying cancer cell biology and facilitating translational research, especially in the identification of drug targets and drug discovery studies. This is particularly relevant in breast cancer, where the global burden of disease is quite high based on prevalence and a relatively high rate of lethality. Predictive tools to select patients who will be responsive to invasive or morbid therapies (radiotherapy, chemotherapy, immunotherapy, and/or surgery) are relatively lacking. To be clinically relevant, a model must accurately replicate the biology and cellular heterogeneity of the primary tumor. Addressing these requirements and overcoming the limitations of most existing cancer cell lines, which are typically derived from a single clone, we have recently developed conditional reprogramming (CR) technology. The CR technology refers to a co-culture system of primary human normal or tumor cells with irradiated murine fibroblasts in the presence of a Rho-associated kinase inhibitor to allow the primary cells to acquire stem cell properties and the ability to proliferate indefinitely in vitro without any exogenous gene or viral transfection. This innovative approach fulfills many of these needs and offers an alternative that surpasses the deficiencies associated with traditional cancer cell lines. These CR cells (CRCs) can be reprogrammed to maintain a highly proliferative state and reproduce the genomic and histological characteristics of the parental tissue. Therefore, CR technology may be a clinically relevant model to test and predict drug sensitivity, conduct gene profile analysis and xenograft research, and undertake personalized medicine. This review discusses studies that have applied CR technology to conduct breast cancer research.

Coiled carbon nanotubes (CCNTs) as a promising nanometer scale spring are investigated for the effect of the defects on the tensile mechanical properties of CCNTs by using molecular dynamics (MD) simulations. Six samples of defective CCNTs are constructed by introducing the defects in the different positions. The results show an obvious decrease in the spring constant and elastic limit of defective CCNTs, which results in the lower energy storage ability during the elastic range compared with the perfect CCNTs. However, the defected CCNTs exhibit better ductility (138.9%) and higher energy absorbing ability (1539.93 J/g) during the fracture process since introduced defects change the deformation pattern. Furthermore, among the defected CCNTs, the stiffness (1.48~1.93 nN/nm), elastic limit (75.2~88.7%), ductility (108.5~138.9%), and deformation pattern can be adjusted by changing the position or the type of defects. This study firstly provides insight into the effects of Stone–Wales (SW) and vacancy defects on the mechanical properties of CCNTs, and the obtained results are meaningful for designing CCNTs with specified properties by introducing defects.

Abstract Networks based on carbon nanotube (CNT) have been widely utilized to fabricate flexible electronic devices, but defects inevitably exist in these structures. In this study, we investigate the influence of the CNT-unit defects on the mechanical properties of a honeycomb CNT-based network, super carbon nanotube (SCNT), through molecular dynamics simulations. Results show that tensile strengths of the defective SCNTs are affected by the defect number, distribution continuity and orientation. Single-defect brings 0 ~ 25% reduction of the tensile strength with the dependency on defect position and the reduction is over 50% when the defect number increases to three. The distribution continuity induces up to 20% differences of tensile strengths for SCNTs with the same defect number. A smaller arranging angle of defects to the tensile direction leads to a higher tensile strength. Defective SCNTs possess various modes of stress concentration with different concentration degrees under the combined effect of defect number, arranging direction and continuity, for which the underlying mechanism can be explained by the effective crack length of the fracture mechanics. Fundamentally, the force transmission mode of the SCNT controls the influence of defects and the cases that breaking more force transmission paths cause larger decreases of tensile strengths. Defects are non-negligible factors of the mechanical properties of CNT-based networks and understanding the influence of defects on CNT-based networks is valuable to achieve the proper design of CNT-based electronic devices with better performances. Graphical Abstract

Optimal land management practices could increase terrestrial carbon sequestration by 13.7 Petagrams of carbon each year, with only 15% of the land area accounting for half of this increase, according to a carbon gap analysis of global primary production.

An AlGaInAs multiple-quantum-well (MQW) polarization mode controller (PMC) using a stepped height ridge waveguide is presented, which is monolithically integrated with a sidewall grating distributed feedback laser using quantum well intermixing (QWI). QWI is used to create a 100 nm blueshift in the PMC and to partially eliminate the anisotropy and birefringence of the MQW structure. The PMC structure is modelled and optimized using a 3D full-vectorial Finite-Element Method package. The maximum polarization conversion efficiency (PCE) is around 96% for a 537-μm-long PMC operating at a wavelength of 1550 nm. To maintain a PCE of ≥90%, the fabrication tolerances of the dry-etch corner and ridge waveguide widths are ± 0.05 μm and ± 0.03 μm respectively. The main advantages of the proposed design are that only a single step of MOPVE and two steps of dry etching are required for the whole integrated device, significantly reducing complexity and cost.