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Raffaella Devescovi,1 Lorenzo Monasta,2 Alice Mancini,3 Maura Bin,1 Valerio Vellante,1 Marco Carrozzi,1 Costanza Colombi4 1Division of Child Neurology and Psychiatry, 2Clinical Epidemiology and Public Health Research Unit, Institute for Maternal and Child Health – IRCCS “Burlo Garofolo”, Trieste, 3Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy; 4Department of Psychiatry, University of Michigan Health System, Ann Arbor, MI, USA Background: Early diagnosis combined with an early intervention program, such as the Early Start Denver Model (ESDM), can positively influence the early natural history of autism spectrum disorders. This study evaluated the effectiveness of an early ESDM-inspired intervention, in a small group of toddlers, delivered at low intensity by the Italian Public Health System.Methods: Twenty-one toddlers at risk for autism spectrum disorders, aged 20–36 months, received 3 hours/wk of one-to-one ESDM-inspired intervention by trained therapists, combined with parents’ and teachers’ active engagement in ecological implementation of treatment. The mean duration of treatment was 15 months. Cognitive and communication skills, as well as severity of autism symptoms, were assessed by using standardized measures at pre-intervention (Time 0 [T0]; mean age =27 months) and post-intervention (Time 1 [T1]; mean age =42 months).Results: Children made statistically significant improvements in the language and cognitive domains, as demonstrated by a series of nonparametric Wilcoxon tests for paired data. Regarding severity of autism symptoms, younger age at diagnosis was positively associated with greater improvement at post-assessment.Conclusion: Our results are consistent with the literature that underlines the importance of early diagnosis and early intervention, since prompt diagnosis can reduce the severity of autism symptoms and improve cognitive and language skills in younger children. Particularly in toddlers, it seems that an intervention model based on the ESDM principles, involving the active engagement of parents and nursery school teachers, may be effective even when the individual treatment is delivered at low intensity. Furthermore, our study supports the adaptation and the positive impact of the ESDM entirely sustained by the Italian Public Health System. Keywords: early diagnosis, early intervention, autism spectrum disorder, Early Start Denver Model, Public Health System service

Managing quality education primarily for children with special needs has been a challenge for the Indonesian government, and it has enhanced attention among scholars. This study aims to investigate the determinant factors driving the success of the implementation of inclusive education in Indonesia. This study involves the variables that directly link with the implementation of inclusive education, including teachers, school principals, and parents. The research involved a mixedmethod approach to reach a deeper understanding of this phenomenon. This study started with quantitative data and was followed by qualitative analysis. The data were collected using questionnaires and further conducted in-depth interviews for selected informants in East Java of Indonesia. The results indicate that the highest supports come from special teachers, followed by parents and teacher in other subjects. Surprisingly, school principals take the lowest rank for implementing inclusive education in East Java of Indonesia. The implication of this study is to collaborate between parties can enhance the success of inclusive education implementation in Indonesia.

Abstract Leveraging its ability to handle large and complex datasets, artificial intelligence can uncover subtle patterns and correlations that human observation may overlook. This is particularly valuable for understanding the intricate dynamics of spinal surgery and its multifaceted impacts on patient prognosis. This review aims to delineate the role of artificial intelligence in spinal surgery. A search of the PubMed database from 1992 to 2023 was conducted using relevant English publications related to the application of artificial intelligence in spinal surgery. The search strategy involved a combination of the following keywords: "Artificial neural network," "deep learning," "artificial intelligence," "spinal," "musculoskeletal," "lumbar," "vertebra," "disc," "cervical," "cord," "stenosis," "procedure," "operation," "surgery," "preoperative," "postoperative," and "operative." A total of 1,182 articles were retrieved. After a careful evaluation of abstracts, 90 articles were found to meet the inclusion criteria for this review. Our review highlights various applications of artificial neural networks in spinal disease management, including (1) assessing surgical indications, (2) assisting in surgical procedures, (3) preoperatively predicting surgical outcomes, and (4) estimating the occurrence of various surgical complications and adverse events. By utilizing these technologies, surgical outcomes can be improved, ultimately enhancing the quality of life for patients.

Nouf Aloudah,1 Raghad Abdulaziz Alsaja,2 Abeer Mohammed Bin Mohareb,2 Aljoharah O Alshabanah,2 Raghad Bakr Alammari2 1Clinical Pharmacy Department, King Saud University, Riyadh, Saudi Arabia; 2College of Pharmacy, King Saud University, Riyadh, Saudi ArabiaCorrespondence: Nouf Aloudah, Email naloudah@ksu.edu.saIntroduction: Improper disposal of unused antibiotics poses a significant global challenge, drawing attention from various stakeholders. This discharge of antibiotics into the environment can occur through various means such as industrial production, consumption, and excretion by humans and animals, as well as improper disposal of unused or expired antibiotics. The aim of our study is to investigate the availability of proper disposal of antibiotics in community pharmacies and to explore obstacles and opportunities from pharmacist’s point of view.Methods: This study used a mixed-methods approach that consisted of two study arms: quantitative and qualitative. The quantitative arm used a mystery-shopper method for assessing the disposal of antibiotics in community pharmacies. The qualitative study arm consisted of several in-depth semi-structured focus groups with a sample of pharmacists working in community pharmacies in Riyadh.Results: The mystery shopper arm showed that 85% (n=88) refused to take the return of antibiotics. Interviews with pharmacists have indicated a lack of knowledge on safe disposal methods for antibiotics and medications. Additionally, pharmacists have cited several factors contributed to accumulation of the antibiotics such as nonadherence or policies mandating the sale of whole medication packs instead of the required amounts as a contributing factor to this issue. Furthermore, there is a lack of dedicated facilities for the population to safely dispose of their medications and/antibiotics.Conclusion: By acknowledging the factors contributing to improper disposal practices, recognizing the importance of proper antibiotic disposal, and advocating for multi-faceted initiatives, we can work towards mitigating this critical issue. Through collaborative efforts involving education, policy interventions, and community engagement, we can foster a culture of responsible medication disposal, ultimately safeguarding public health and environmental well-being.Keywords: antibiotic disposal, antibiotic waste, Saudi Arabia, unused antibiotics, health care professionals, mixed methods, mystery shoppers, qualitative research, in-depth interviews

Abstract Ensuring operational integrity in large-scale equipment hinges on effective fault prediction and health management. Prognostics and health management (PHM) face the challenge of accurately predicting remaining useful life (RUL) using multivariate sensor data. Traditional methods often require extensive prior knowledge for indicator construction and processing. Deep learning offers a promising alternative. This study presents a multi-channel multi-scale deep learning approach. Initially, an improved Savitzky‒Golay filter (ISG) addresses challenges posed by large and rapidly changing data volumes, enhancing data preprocessing. Subsequently, a framework integrates convolutional neural networks (CNNs) with long short-term memory (LSTM) to capture hierarchical signal information and make integrated predictions. The CNN extracts spatial features from multi-channel input data, while the LSTM captures temporal dependencies. By fusing outputs from both components, the framework enhances predictive accuracy and robustness for complex operational datasets. Experimental validation on the C-MAPSS dataset tests various fusion methods and CNN depths, determining parameters and evaluating filtering effectiveness. Comparative analyses show promising performance, particularly under dynamic conditions. While not optimal for predicting multiple fault types, it outperforms classical algorithms, especially in single fault type prediction tasks.

Abstract The antibody response to vaccination and infection is a key component of the immune response to pathogens. Sequencing of peripheral B cells may not represent the complete B cell receptor repertoire. Here we present a method for sequencing human plasma-derived polyclonal IgG using a combination of mass spectrometry and B-cell sequencing. We investigate the IgG response to the Moderna Spikevax COVID-19 vaccine. From the sequencing data of the natural polyclonal response to vaccination, we generate 12 recombinant antibodies. Six derived recombinant antibodies, including four generated with de novo protein sequencing, exhibit similar or higher binding affinities than the original natural polyclonal antibody. Neutralization tests reveal that the six antibodies possess neutralizing capabilities against the target antigen. This research provides insights into sequencing polyclonal IgG antibodies and the potential of our approach in generating recombinant antibodies with robust binding affinity and neutralization capabilities. Directly examining the circulating IgG pool is crucial due to potential misrepresentations by B-cell analysis alone.

Abstract Necrotizing fasciitis (NF) is a rare and life-threatening serious infectious disease, characterized by acute onset and rapid progress, leading to extensive necrosis of skin, soft tissue as well as fascia by a variety of aerobic and anaerobic bacteria, localized on external genitalia, scrotum, groin and perianal areas in males. There exist numerous common etiologies for NF, yet NF induced by malignant neoplasms is exceedingly rare. Several studies have reported that NF may be associated with tumor site (rectal/sigmoid colon cancer) and blood supply dysfunction caused by targeted therapy drugs (bevacizumab, aflibercept, ramucirumab). The perforation of colorectal cancer poses a unique risk factor for NF. However, in our two cases, the patient with rectal cancer received CapeOX (oxaliplatin + capecitabine) + bevacizumab + tislelizumab for 3 cycles without perforation but did develop NF. One month after debridement, the patient continued immunotherapy with tislelizumab alone for the fourth cycle and maintained for an additional 3 cycles without any recurrence of NF. Therefore, does the occurrence of NF correlate with the tumor site (rectum) and targeted immunotherapy? Another patient with hepatocellular carcinoma also developed NF after receiving 2 cycles of lenvatinib + sintilimab treatment. The third cycle of sintilimab immunotherapy was administered on the 13th day after operation, which was subsequently maintained for an additional 2 cycles without recurrence of NF. The absence of a direct correlation between hepatocellular carcinoma and rectal tumor location as well as immunotherapy, suggests that NF may be closely linked to targeted therapy.

Abstract Purpose To investigate the role of Actin like 6 A (ACTL6A) in cancer and explore the potential mechanism of its function. Methods Differential expression of ACTL6A was analyzed using Oncomine and TIMER database. Then, we downloaded data sets from TCGA database. The correlation between ACTL6A expression and survival in pan-cancer were analyzed by “survival”, “survminer” R package and PrognoScan database. STRING (v 11.0) and stringAPP for Cytoscape v3.7.2 were used to predict ACTL6A associated genes. Copy number and methylation alterations of ACTL6A were analyzed using cBioPortal and GSCALite. Transcription factors were downloaded from The Human Transcription Factors Database and analyzed using “limma” R package, JASPAR and PROMO database. Correlations analysis between ACTL6A and immune cells were performed using TIMER and GEPIA database. Results In our studies, we found that ACTL6A was widely upregulated in cancers, which might be attributed to its gene amplifications. Moreover, ACTL6A might regulated by transcription factors (TFs), including E2F1, YY1, CDX2 and HOXD10. In addition, high ACTL6A expression was associated with poor prognosis in most cancers. Meanwhile, ACTL6A was associated with the infiltration of immune cells, especially in liver hepatocellular carcinoma and brain lower grade glioma. Conclusion Amplification of ACTL6A is correlated with poor prognosis and contribute to immune cells infiltration in LIHC and LGG, which may provide immune-related therapeutic targets to guide clinical strategies.

Abstract Global urbanization requires more stable and sustainable wastewater treatment to reduce the burden on the water environment. To address the problem of substrate inhibition of microorganisms during wastewater treatment, which leads to unstable wastewater discharge, this study proposes an approach to enhance the tolerance of bacterial community by artificially setting up a non-lethal high substrate environment. And the feasibility of this approach was explored by taking the inhibition of anammox process by nitrite as an example. It was shown that the non-lethal high substrate environment could enhance the nitrite tolerance of anammox bacterial community, as the specific anammox activity increasing up to 24.71 times at high nitrite concentrations. Moreover, the system composed of anammox bacterial community with high nitrite tolerance also showed greater resistance (two-fold) in response to nitrite shock. The antifragility of the system was enhanced without affecting the operation of the main reactor, and the non-lethal high nitrite environment changed the dominant anammox genera to Candidatus Jettenia. This approach to enhance tolerance of bacterial community in a non-lethal high substrate environment not only allows the anammox system to operate stably, but also promises to be a potential strategy for achieving stable biological wastewater treatment processes to comply with standards.

Abstract While deep learning models have shown promising capabilities in ENSO prediction, their inherent black-box nature often leads to a lack of physical consistency and interpretability. Here, we introduce ENSO-PhyNet, a Transformer-based model for ENSO prediction, which incorporates heat budget dynamical processes through self-attention computations. The model predicts sea surface temperature (SST) in the equatorial Pacific and achieves skillful predictions of the Niño 3.4 index with a lead time of up to 22 months. The self-attention maps reveal how the model makes predictions by focusing on specific processes in certain regions. Case analyses of recent El Niño and La Niña events underscore the impact of thermocline feedback and zonal advection feedback on the warming of the 2015 event, as well as the crucial role of anomalous easterlies in the emergence of the second-year La Niña in 2021. These findings demonstrate the model’s interpretability and its ability to identify signals that are physically consistent with the development of ENSO events.

Abstract Early, rapid, and accurate diagnostic tests play critical roles not only in the identification/management of individuals infected by SARS-CoV-2, but also in fast and effective public health surveillance, containment, and response. Our aim has been to develop a fast and robust fluorescence in situ hybridization (FISH) detection method for detecting SARS-CoV-2 RNAs by using an HEK 293 T cell culture model. At various times after being transfected with SARS-CoV-2 E and N plasmids, HEK 293 T cells were fixed and then hybridized with ATTO-labeled short DNA probes (about 20 nt). At 4 h, 12 h, and 24 h after transfection, SARS-CoV-2 E and N mRNAs were clearly revealed as solid granular staining inside HEK 293 T cells at all time points. Hybridization time was also reduced to 1 h for faster detection, and the test was completed within 3 h with excellent results. In addition, we have successfully detected 3 mRNAs (E mRNA, N mRNA, and ORF1a (−) RNA) simultaneously inside the buccal cells of COVID-19 patients. Our high-resolution RNA FISH might significantly increase the accuracy and efficiency of SARS-CoV-2 detection, while significantly reducing test time. The method can be conducted on smears containing cells (e.g., from nasopharyngeal, oropharyngeal, or buccal swabs) or smears without cells (e.g., from sputum, saliva, or drinking water/wastewater) for detecting various types of RNA viruses and even DNA viruses at different timepoints of infection.

Abstract Tumour detection with high selectivity and sensitivity is crucial for delineating tumour margins and identifying metastatic foci during image-guided surgery. Optical nanoprobes with preferential tumour accumulation is often limited by inefficient amplification of biological signals. Here, we report the design of a library of hydrophobic core-tunable ultra-pH-sensitive nanoprobes (HUNPs) for orthogonally amplifying tumour microenvironmental signals on multiple tumour models. We find that tuning the hydrophobicity of nanoparticle core composition with non-ionizable monomers can enhance cellular association of HUNPs by more than ten-fold, resulting in a high cellular internalization efficiency of HUNPs with up to 50% in tumours. Combining high tumour accumulation and high cell internalization efficiency, HUNPs show orthogonally amplified fluorescence signals, permitting the precise locating and delineating margins between malignant lesions and normal tissues with high contrast-to-noise ratio and resolution. Our study provides key strategies to design nanomedicines with high intracellular bioavailability for cancer detection, drug/gene delivery, and therapy.

Abstract Background For youths, abnormalities in ambulatory blood pressure (ABP) patterns are known to be associated with increased cardiovascular disease risk and potential target organ damage. Body composition, including indicators such as lean mass index (LMI), fat mass index (FMI), and visceral fat level (VFL), plays a significant role in blood pressure (BP) regulation. However, little is known about the association between these body composition indicators and ABP. Therefore, the present study examined the association between these body composition indicators and BP among Chinese youths. Methods A total of 477 college students aged 17 to 28 years old (mean ± Standard deviation = 18.96 ± 1.21) from a university in Changsha, Hunan Province, China, were included in this study. Body composition indicators were measured with a bioelectrical impedance body composition analyzer, and 24-hour ambulatory blood pressure monitoring (ABPM) was conducted. Multivariable logistic regression was performed to assess the relationship between body composition indicators and abnormal ABP. Results The prevalence of abnormal BP, including 24-hour BP, daytime BP, nighttime BP, and clinic BP, were 4.8%, 4.2%, 8.6%, and 10.9%, respectively. After adjusting for potential covariates, LMI [abnormal 24-hour BP (OR = 1.85, 95%CI:1.31, 2.62), abnormal daytime BP (OR = 1.76, 95%CI:1.21, 2.58), abnormal nighttime BP (OR = 1.64, 95%CI:1.25, 2.14), abnormal clinic BP (OR = 1.84, 95%CI:1.38, 2.45)], FMI [abnormal 24-hour BP (OR = 1.20, 95%CI:1.02, 1.41), abnormal daytime BP (OR = 1.30, 95%CI:1.07, 1.57), abnormal nighttime BP (OR = 1.24, 95%CI:1.10, 1.39), abnormal clinic BP (OR = 1.42, 95%CI:1.22, 1.65)], and VFL [abnormal 24-hour BP (OR = 1.22, 95%CI:1.06, 1.39), abnormal daytime BP (OR = 1.29, 95%CI:1.10, 1.51), abnormal nighttime BP (OR = 1.24, 95%CI:1.12, 1.39), abnormal clinic BP (OR = 1.38, 95%CI:1.21, 1.57)] are positively linked to abnormal BP. Additionally, there were significant sex differences in the association between body composition and abnormal BP. Conclusions Our findings suggested maintaining an individual’s appropriate muscle mass and fat mass and focusing on the different relations of males’ and females’ body composition is crucial for the achievement of appropriate BP profiles.

Abstract Metabolic dysfunction-associated steatohepatitis (MASH) poses challenges for targeted delivery and retention of therapeutic proteins due to excess extracellular matrix (ECM). Here we present a new approach to treat MASH, termed “Fibrosis overexpression and retention (FORT)”. In this strategy, we design (1) retinoid-derivative lipid nanoparticle (LNP) to enable enhanced mRNA overexpression in fibrotic regions, and (2) mRNA modifications which facilitate anchoring of therapeutic proteins in ECM. LNPs containing carboxyl-retinoids, rather than alcohol- or ester-retinoids, effectively deliver mRNA with over 10-fold enhancement of protein expression in fibrotic livers. The carboxyl-retinoid rearrangement on the LNP surface improves protein binding and membrane fusion. Therapeutic proteins are then engineered with an endogenous collagen-binding domain. These fusion proteins exhibit increased retention in fibrotic lesions and reduced systemic toxicity. In vivo, fibrosis-targeting LNPs encoding fusion proteins demonstrate superior therapeutic efficacy in three clinically relevant male-animal MASH models. This approach holds promise in fibrotic diseases unsuited for protein injection.

It has been studied that both two-dimensional (2D) MoS2 and V2O5, which are classified as transition metal dichalcogenides and transition metal oxides, are good photocatalyst materials. For this purpose, the hydrothermal method was practiced to synthesize V2O5(1−x)MoS2(x) (X = 1–5% w/w) nanocomposites with different 1–5% w/w weight percent of MoS2 as a prominent photocatalyst under laser irradiation for 2, 4, 6, 8, and 10 min to tune photocatalytic degradation of industrial wastage water. The surface of the 2D molybdenum nanolayered matrix was efficaciously decorated with V2O5 nanoparticles. The crystal phase and layered structures of the V2O5(1−x)MoS2(x) (X = 1–5% w/w) nanocomposites samples were verified by X-ray diffraction and scanning electron microscopy, atomic force microscopy, X-ray photoelectron spectroscopy respectively. In the range of the UV visible spectrum, the increment in light absorption from 3.6 to 14.5 Ω−1 cm−1 with an increase of active surface from 108 to 169 μm2{{\rm{\mu }}{\rm{m}}}^{2} with increased MoS2 doping percentage. Furthermore, dielectric findings like the complex dielectric function, tangent loss, electrical conductivity, quality factors, and impedance of V2O5(1−x)MoS2(x) (X = 1–5% w/w) nanocomposites are studied. According to photoluminescence studies, the intensity of peaks decreases when laser irradiation time and doping percentages of MoS2 are increased. As a result, a small peak indicates a decrement rate of electron–hole pair recombination, which increases the capacity for separation. Thermo-gravimetric analysis and differential thermal analysis results revealed that weight loss decreased from 0.69 to 0.35 mg and thermal stability increased with increased doping concentrations. Methylene blue was degraded in 150 min, proving that the prepared MoS2-doped V2O5 material was a stable and economically low-cost nanocomposite for photocatalytic activity.

Objective To investigate the use of anti‐osteoporotic agents and refracture incidence in patients with osteoporotic vertebral compression fracture (OVCF) following percutaneous vertebral augmentation (PVA) and to evaluate the real‐world treatment of patients using denosumab following PVA. This study aims to provide spine surgeons with empirical insights derived from real‐world scenarios to enhance the management of bone health in OVCF patients. Methods This retrospective cohort study was based on data from the MarketScan and Optum databases from the USA. Female patients aged 55–90 years who underwent PVA for OVCF between January 2013 and March 2020 were included and followed up from the day after surgery. Patients who received at least one dose of denosumab were included in the denosumab cohort and were further divided into the on‐treatment and off‐treatment groups according to whether they received a second dose of denosumab, with follow‐up beginning on the index day (225 days after the first denosumab dose). In this study, the off‐treatment group was considered as the control group. Refracture incidence after PVA, the proportion of patients using anti‐osteoporotic agents in the total study population, and refracture incidence after the index day in the denosumab cohort were analyzed. Results A total of 13,451 and 21,420 patients from the MarketScan and Optum databases, respectively, were included. In the denosumab cohort, the cumulative incidence of clinical osteoporotic fractures within 3 years after the index day was significantly lower in the on‐treatment group than in the off‐treatment group (MarketScan database: 23.0% vs 39.0%, p = 0.002; Optum database: 28.2% vs 40.0%, p = 0.023). The cumulative incidence of clinical vertebral fractures was also lower in the on‐treatment group than in the off‐treatment group, with a significant difference in the MarketScan database (14.4% vs 25.5%, p = 0.002) and a numerical difference was found in the Optum database (20.2% vs 27.5%, p = 0.084).The proportion of patients using anti‐osteoporotic agents was low at 6 months postoperatively, with only approximately 7% using denosumab and 13%–15% taking oral bisphosphonates. Conclusion Postmenopausal women have a high refracture rate and a low proportion of anti‐osteoporotic drug use after PVA. Continued denosumab treatment after PVA is associated with a lower risk of osteoporotic and clinical vertebral fractures. Therefore, denosumab may be a treatment option for patients with osteoporosis after PVA.

Three new rare-earth high-entropy oxides with compositions of (Y1/7La1/7Nd1/7Sm1/7Gd1/7Yb1/7Lu1/7)2O3 (7HEO), (Y1/8La1/8Nd1/8Sm1/8Gd1/8Yb1/8Lu1/8Ce1/8)2O3 (8HEO) and (Y1/10La1/10Nd1/10Sm1/10Gd1/10Yb1/10Lu1/10Ce1/10Zr1/10Hf1/10)2O3 (10HEO) were prepared using a solid-state reaction method combined with conventional sintering at 1600 °C for 10 h 7HEO has a monoclinic structure. The addition of Ce into 7HEO not only leads to the phase transformation from monoclinic to bixbyite structure, but also contributes to the grain refinement. When the three elements of Ce, Zr and Hf are added into 7HEO, a second fluorite-structured phase forms and further promotes the grain refinement. 10HEO and 8HEO have a higher thermal conductivity compared with 7HEO in 25–600 °C. When the temperature reaches 900 °C, the thermal conductivity of 8HEO is lower than that of 7HEO. The addition of Ce or Ce/Zr/Hf into 7HEO causes the weakening of the bond strength and the increase of the bond length of cation-O2- in the samples, which in turn increases the thermal expansion coefficient. Moreover, 7HEO possesses a better oxygen barrier property compared with 8HEO and 10HEO. The hardness and Young's modulus of 7HEO are lower than those of 8HEO and 10HEO.

Abstract Cement-based materials are integral to radioactive waste repositories, providing versatile solutions for diverse disposal strategies. They are part of the multi-barrier system, and serve to immobilize waste materials, limit the release of radionuclides, contribute to an alkaline near-field to inhibit steel corrosion, reduce microbial activity, and slow down radionuclide transport in the repository near-field. This work delves into the adaptability of the multi-barrier systems for long-term safety, examining cases in clay and granite. Highlighting the disposal case in clay, the study emphasizes the role of cement in ensuring repository stability. The barrier system aims to minimize radionuclide release and demonstrate long-term isolation and containment of waste. The containment duration is relevant to the radionuclide’s half-life, with consideration for extended safety over extremely long periods. Cement evolves under geological conditions, undergoing a progressive process of degradation that is influenced by intricate aggregate-cement reactions and external factors, e.g., sulfates and chlorides in groundwater, the host rocks (including clays and granites), and the engineered barrier materials (including bentonite and steel), and in turn influencing mechanical stress generation and porosity. The very slow chemical alteration processes that take place at the concrete/granite interface underscore the repository stability. Corrosion of steel in the cement is expected to be slow, but its long-term structural and chemical changes remain quite unknown. Challenges remain in accurately predicting the long-term performance of the cement due to uncertainties in chemical reactivity, the impact of partial water saturation, and the kinetics of degradation processes. The manuscript advances the development of predictive modeling tools for assessing the long-term performance of cement-based barriers. The integration of experimental results with modeling efforts offers a robust framework for predicting the behavior of cementitious materials under various environmental conditions, thereby contributing to more reliable safety assessments of radioactive waste repositories. The role of cement phases in ensuring repository safety remains pivotal.

Abstract The synthesis of chiral α-azaheteroaryl oxiranes via enantioselective catalysis is a formidable challenge due to the required complex stereoselectivity and diverse N-heterocyclic structures. These compounds play a crucial role in developing bioactive molecules, where precise chirality significantly influences biological activity. Here we show that using chiral phosphoric acid as a catalyst, our method efficiently addresses these challenges. This technique not only achieves high enantio- and diastereoselectivity but also demonstrates superior chemo- and stereocontrol during the epoxidation of alkenyl aza-heteroarenes. Our approach leverages a synergistic blend of electrostatic and hydrogen-bonding interactions, enabling the effective activation of both substrates and hydrogen peroxide. The resulting chiral oxiranes exhibit enhanced diversity and functionality, aiding the construction of complex chiral azaaryl compounds with contiguous stereocenters. Kinetic and density functional theory studies elucidate the mechanism, highlighting chiral phosphoric acid’s pivotal role in this intricate enantioselective process.

Abstract Although aspirin can reduce the incidence of colorectal cancer (CRC), there is still uncertainty about its significance as a treatment for CRC, and the mechanism of aspirin in CRC is not well understood. In this study, we used aspirin to prevent AOM/DSS-induced CRC in mice, and the anti-CRC efficacy of aspirin was assessed using haematoxylin and eosin (H&E) staining and by determining the mouse survival rate and tumour size. 16S rDNA sequencing, flow cytometry (FCM), and Western blotting were also conducted to investigate the changes in the gut microbiota, tumour immune microenvironment, and apoptotic proteins, respectively. The results demonstrated that aspirin significantly exerted anti-CRC effects in mice. According to 16S rDNA sequencing, aspirin regulated the composition of the gut microbiota and dramatically reduced the abundance of Enterococcus cecorum. FCM demonstrated that there were more CD155 tumour cells and CD4 + CD25 + Treg cells showed increased TIGIT levels. Moreover, increased TIGIT expression on Treg cells is associated with reduced Treg cell functionality. Importantly, the inhibition of Treg cells is accompanied by the promotion of CD19 + GL-7 + B cells, CD8 + T cells, CD4 + CCR4 + Th2 cells, and CD4 + CCR6 + Th17 cells. Overall, aspirin prevents colorectal cancer by regulating the abundance of Enterococcus cecorum and TIGIT + Treg cells.

Abstract Obesity is accompanied by multiple known health risks and increased morbidity, and obese men display reduced reproductive health. However, the impact of obesity on the testes at the molecular levels remain inadequately explored. This is partially attributed to the lack of monitoring tools for tracking alterations within cell clusters in testes associated with obesity. Here, we utilized single-cell RNA sequencing to analyze over 70,000 cells from testes of obese and lean mice, and to study changes related to obesity in non-spermatogenic cells and spermatogenesis. The Testicular Library encompasses all non-spermatogenic cells and spermatogenic cells spanning from spermatogonia to spermatozoa, which will significantly aid in characterizing alterations in cellular niches and the testicular microenvironment during high-fat diet (HFD)-induced obesity. This comprehensive dataset is indispensable for studying how HFD disrupts cell-cell communication networks within the testis and impacts alterations in the testicular microenvironment that regulate spermatogenesis. Being the inaugural dataset of single-cell RNA-seq in the testes of diet-induced obese (DIO) mice, this holds the potential to offer innovative insights and directions in the realm of single-cell transcriptomics concerning male reproductive injury associated with HFD.

Abstract Silent speech recognition (SSR) based on surface electromyography (sEMG) is a voice interaction technology proposed for scenarios requiring silent operations. This article abstracts the SSR task based on sEMG into a short‐term image sequence classification task. Time‐frequency domain feature extraction and data reconstruction on the muscle activity segment data is performed. Additionally, the temporal and spatial dimensions to capture the intrinsic correlation representation of muscle activity is analysed. The SVIT‐SSR model is proposed based on the vision transformer (VIT) framework. Finally, experiments to identify 33 types of typical silent speech commands in the SSR dataset are designed. The results demonstrate that the proposed model achieves an accuracy of 96.67 ± 1.15%, outperforming similar algorithms.