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Abstract Background An umbrella review of meta-analyses was conducted to evaluate the use of platelet-rich plasma (PRP) in arthroscopic surgeries of rotator cuff injury. The effectiveness of leukocyte-poor PRP and leukocyte-rich PRP in the treatment of rotator cuff surgery was also compared. Methods Web of Science, Embase, PubMed/MEDLINE, and the Cochrane Library were searched from inception to May 2024. Literature screening, quality evaluation, and data extraction were performed according to the inclusion and exclusion criteria. The Jadad decision algorithm was used to ascertain which meta-analysis represented the best evidence. Results A total of 11 meta-analyses with evidence level ranging from level 1 to 2 were included in this umbrella review. Leukocyte-poor PRP was effective in reducing rotator cuff retear rates, alleviating pain, and increasing Constant scores compared with non-PRP treatments. However, it did not show improvement on the University of California Los Angeles (UCLA) score, the American Shoulder and Elbow Surgeons (ASES) score, and the Simple Shoulder Test (SST) compared with the non-PRP treatment group. Meanwhile, the leukocyte-rich PRP group improved the SST but showed no different results when compared with the non-PRP treatment group. Conclusion Compared with no use of PRP, leukocyte-poor PRP was able to alleviate postoperative pain, reduce the retear rate, and improve the postoperative Constant score. Leukocyte-rich PRP could effectively enhance postoperative SST outcomes, leading to improvement of patient satisfaction and quality of life. Future researches should prioritize long-term follow-up studies and evaluate the durability of these results.

Abstract The incidence of lung cancer has become the highest among all cancer types globally, also standing as a leading cause of cancer-related deaths. Lung cancer is broadly divided into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), with the latter accounting for 85% of total cases. SRY-box transcription factor 4 (SOX4), a crucial transcription factor, has been found to play a key role in the development of various cancers. However, the association between SOX4 and NSCLC is still unclear. This study investigated the clinical relevance of SOX4 and its potential mechanisms in the progression of NSCLC. Analysis of our NSCLC patient cohort revealed a significant increase in SOX4 levels in cancerous tissues, indicating its role as an independent prognostic indicator for NSCLC. In vitro experiments demonstrated that elevated SOX4 expression facilitated NSCLC cell migration, invasion, and EMT. Functionally, SOX4 drives NSCLC progression by enhancing the transcription and expression of B-cell-specific moloney leukemia virus insertion site 1 (BMI1). The oncogenic impact of SOX4-induced BMI1 expression on NSCLC advancement was validated through both in vivo and in vitro studies. In addition, our findings showed that BMI1 promoted the ubiquitination of histone H2A (H2Aub), leading to decreased zinc finger protein 24 (ZNF24) expression, which subsequently triggered vascular endothelial growth factor A (VEGF-A) secretion in NSCLC cells, thereby promoting NSCLC angiogenesis. Moreover, we evaluated the therapeutic potential of a BMI1 inhibitor in combination with Bevacizumab for NSCLC treatment using orthotopic models. The data presented in our study reveal a previously unrecognized role of the SOX4-BMI1 axis in promoting NSCLC progression and angiogenesis. This research significantly contributes to our knowledge of the interplay between SOX4 and BMI1 in NSCLC, potentially paving the way for the development of targeted therapies for this disease.

One issue facing teachers who implement model-based instruction within the school system is the tight curricular schedule. The 'lesson objective tension' calls for investigations to address instructional issues such as how to organise modelling-based instruction at the curriculum level which is across multiple units. We investigated the effect of the cyclic curricular design spacing out three modelling-based instruction units with virtual labs over three semesters, each involving 73, 181, and 150 junior high school students, respectively. Results indicate that, overall, the approach of modelling with virtual labs better promoted students' scientific literacy than the traditional instruction did. Specifically, students with low and moderate school science achievements benefitted more as shown in their scientific literacy scores than did the high achievement students. Furthermore, this study found that receiving one unit of modelling-based instruction may not be sufficient to promote students' scientific literacy, whereas the cyclic approach that suggests students receive two or more units of modelling-based instruction with virtual labs spaced over consecutive semesters had significant effects on promoting students' scientific literacy. The results provide insights into when and how modelling-based learning with virtual labs can promote scientific literacy at a curricular level.

We present findings of the detection of Magnesium II (Mg ii, λ = 2796, 2803 Å) absorbers from the early data release of the Dark Energy Spectroscopic Instrument (DESI). DESI is projected to obtain spectroscopy of approximately 3 million quasars (QSOs), of which over 99% are anticipated to be at redshifts greater than z > 0.3, such that DESI would be able to observe an associated or intervening Mg ii absorber illuminated by the background QSO. We have developed an autonomous supplementary spectral pipeline that detects these systems through an initial line-fitting process and then confirms the line properties using a Markov Chain Monte Carlo sampler. Based upon a visual inspection of the resulting systems, we estimate that this sample has a purity greater than 99%. We have also investigated the completeness of our sample in regard to both the signal-to-noise properties of the input spectra and the rest-frame equivalent width (W 0) of the absorber systems. From a parent catalog containing 83,207 quasars, we detect a total of 23,921 Mg ii absorption systems following a series of quality cuts. Extrapolating from this occurrence rate of 28.8% implies a catalog at the completion of the five-year DESI survey that will contain over eight hundred thousand Mg ii absorbers. The cataloging of these systems will enable significant further research because they carry information regarding circumgalactic medium environments, the distribution of intervening galaxies, and the growth of metallicity across the redshift range 0.3 ≤ z < 2.5.

We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4 m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the universe with the baryon acoustic oscillation technique and the growth rate of structure with redshift space distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near-UV to near-infrared (3600-9800 Å) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline's algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project's requirements for redshift performance, with high efficiency and a purity greater than 99% for all target classes.

The Dark Energy Spectroscopic Instrument (DESI) will precisely constrain cosmic expansion and the growth of structure by collecting ∼40 million extragalactic redshifts across ∼80% of cosmic history and one-third of the sky. The Emission Line galaxy (ELG) sample, which will comprise about one-third of all DESI tracers, will be used to probe the universe over the 0.6 < z < 1.6 range, including the 1.1 < z < 1.6 range, which is expected to provide the tightest constraints. We present the target selection for the DESI Survey Validation (SV) and Main Survey ELG samples, which relies on the imaging of the Legacy Surveys. The Main ELG selection consists of a g-band magnitude cut and a (g − r) versus (r − z) color box, while the SV selection explores extensions of the Main selection boundaries. The Main ELG sample is composed of two disjoint subsamples, which have target densities of about 1940 deg−2 and 460 deg−2, respectively. We first characterize their photometric properties and density variations across the footprint. We then analyze the DESI spectroscopic data that have been obtained from 2020 December to 2021 December in the SV and Main Survey. We establish a preliminary criterion for selecting reliable redshifts, based on the [O ii] flux measurement, and assess its performance. Using this criterion, we are able to present the spectroscopic efficiency of the Main ELG selection, along with its redshift distribution. We thus demonstrate that the Main selection 1940 deg−2 subsample alone should provide 400 deg−2 and 460 deg−2 reliable redshifts in the 0.6 < z < 1.1 and the 1.1 < z < 1.6 ranges, respectively.

A key component of the Dark Energy Spectroscopic Instrument (DESI) survey validation (SV) is a detailed visual inspection (VI) of the optical spectroscopic data to quantify key survey metrics. In this paper we present results from VI of the quasar survey using deep coadded SV spectra. We show that the majority (≈70%) of the main-survey targets are spectroscopically confirmed as quasars, with ≈16% galaxies, ≈6% stars, and ≈8% low-quality spectra lacking reliable features. A nonnegligible fraction of the quasars are misidentified by the standard spectroscopic pipeline, but we show that the majority can be recovered using post-pipeline “afterburner” quasar-identification approaches. We combine these “afterburners” with our standard pipeline to create a modified pipeline to increase the overall quasar yield. At the depth of the main DESI survey, both pipelines achieve a good-redshift purity (reliable redshifts measured within 3000 km s−1) of ≈99%; however, the modified pipeline recovers ≈94% of the visually inspected quasars, as compared to ≈86% from the standard pipeline. We demonstrate that both pipelines achieve a median redshift precision and accuracy of ≈100 km s−1 and ≈70 km s−1, respectively. We constructed composite spectra to investigate why some quasars are missed by the standard pipeline and find that they are more host-galaxy dominated (i.e., distant analogs of “Seyfert galaxies”) and/or more dust reddened than the standard-pipeline quasars. We also show example spectra to demonstrate the overall diversity of the DESI quasar sample and provide strong-lensing candidates where two targets contribute to a single spectrum.

Abstract FBXO32, a member of the F-box protein family, is known to play both oncogenic and tumor-suppressive roles in different cancers. However, the functions and the molecular mechanisms regulated by FBXO32 in lung adenocarcinoma (LUAD) remain unclear. Here, we report that FBXO32 is overexpressed in LUAD compared with normal lung tissues, and high expression of FBXO32 correlates with poor prognosis in LUAD patients. Firstly, we observed with a series of functional experiments that FBXO32 alters the cell cycle and promotes the invasion and metastasis of LUAD cells. We further corroborate our findings using in vivo mouse models of metastasis and confirmed that FBXO32 positively regulates LUAD tumor metastasis. Using a proteomic-based approach combined with computational analyses, we found a positive correlation between FBXO32 and the PI3K/AKT/mTOR pathway, and identified PTEN as a FBXO32 interactor. More important, FBXO32 binds PTEN via its C-terminal substrate binding domain and we also validated PTEN as a bona fide FBXO32 substrate. Finally, we demonstrated that FBXO32 promotes EMT and regulates the cell cycle by targeting PTEN for proteasomal-dependent degradation. In summary, our study highlights the role of FBXO32 in promoting the PI3K/AKT/mTOR pathway via PTEN degradation, thereby fostering lung adenocarcinoma progression.

Background/purpose: 3D-printed bone tissue engineering is becoming recognized as a key approach in dentistry for creating customized bone regeneration treatments fitting patients bone defects requirements. 3D bioprinting offers an innovative method to fabricate detailed 3D structures, closely emulating the native bone micro-environment and better bone regeneration. This study aimed to develop an 3D-bioprintable scaffold using a combination of alginate and β-tricalcium phosphate (β-TCP) with the Cellink® BioX printer, aiming to advance the field of tissue engineering. Materials and methods: The physical and biological properties of the resulting 3D-printed scaffolds were evaluated at 10 %, 12 %, and 15 % alginate combined with 10 % β-TCP. The scaffolds were characterized through printability, swelling behavior, degradability, and element analysis. The biological assessment included cell viability, alkaline phosphatase (ALP) activity. Results: 10 % alginate/β-TCP 3D printed at 25 °C scaffold demonstrated the optimal condition for printability, swelling capability, and degradability of cell growth and nutrient diffusion. Addition of β-TCP particles significantly improved the 3D printed material viscosity over only alginate (P

The Dark Energy Spectroscopic Instrument (DESI) survey will measure large-scale structures using quasars as direct tracers of dark matter in the redshift range 0.9 < z < 2.1 and using Lyα forests in quasar spectra at z > 2.1. We present several methods to select candidate quasars for DESI, using input photometric imaging in three optical bands (g, r, z) from the DESI Legacy Imaging Surveys and two infrared bands (W1, W2) from the Wide-field Infrared Survey Explorer. These methods were extensively tested during the Survey Validation of DESI. In this paper, we report on the results obtained with the different methods and present the selection we optimized for the DESI main survey. The final quasar target selection is based on a random forest algorithm and selects quasars in the magnitude range of 16.5 < r < 23. Visual selection of ultra-deep observations indicates that the main selection consists of 71% quasars, 16% galaxies, 6% stars, and 7% inconclusive spectra. Using the spectra based on this selection, we build an automated quasar catalog that achieves a fraction of true QSOs higher than 99% for a nominal effective exposure time of ∼1000 s. With a 310 deg−2 target density, the main selection allows DESI to select more than 200 deg−2 quasars (including 60 deg−2 quasars with z > 2.1), exceeding the project requirements by 20%. The redshift distribution of the selected quasars is in excellent agreement with quasar luminosity function predictions.

The Dark Energy Spectroscopic Instrument (DESI) is carrying out a five-year survey that aims to measure the redshifts of tens of millions of galaxies and quasars, including 8 million luminous red galaxies (LRGs) in the redshift range 0.4 < z ≲ 1.0. Here we present the selection of the DESI LRG sample and assess its spectroscopic performance using data from Survey Validation (SV) and the first two months of the Main Survey. The DESI LRG sample, selected using g, r, z, and W1 photometry from the DESI Legacy Imaging Surveys, is highly robust against imaging systematics. The sample has a target density of 605 deg−2 and a comoving number density of 5 × 10−4 h3 Mpc−3 in 0.4 < z < 0.8; this is a significantly higher density than previous LRG surveys (such as SDSS, BOSS, and eBOSS) while also extending to z ∼ 1. After applying a bright star veto mask developed for the sample, 98.9% of the observed LRG targets yield confident redshifts (with a catastrophic failure rate of 0.2% in the confident redshifts), and only 0.5% of the LRG targets are stellar contamination. The LRG redshift efficiency varies with source brightness and effective exposure time, and we present a simple model that accurately characterizes this dependence. In the appendices, we describe the extended LRG samples observed during SV.

The Dark Energy Spectroscopic Instrument (DESI) Survey has obtained a set of spectroscopic measurements of galaxies to validate the final survey design and target selections. To assist in these tasks, we visually inspect DESI spectra of approximately 2500 bright galaxies, 3500 luminous red galaxies (LRGs), and 10,000 emission-line galaxies (ELGs) to obtain robust redshift identifications. We then utilize the visually inspected redshift information to characterize the performance of the DESI operation. Based on the visual inspection (VI) catalogs, our results show that the final survey design yields samples of bright galaxies, LRGs, and ELGs with purity greater than 99%. Moreover, we demonstrate that the precision of the redshift measurements is approximately 10 km s−1 for bright galaxies and ELGs and approximately 40 km s−1 for LRGs. The average redshift accuracy is within 10 km s−1 for the three types of galaxies. The VI process also helps improve the quality of the DESI data by identifying spurious spectral features introduced by the pipeline. Finally, we show examples of unexpected real astronomical objects, such as Lyα emitters and strong lensing candidates, identified by VI. These results demonstrate the importance and utility of visually inspecting data from incoming and upcoming surveys, especially during their early operation phases.

Bardet–Biedl syndrome is a rare autosomal recessive genetic disorder with heterogenous clinical manifestations. The present study reports the clinical features of a novel compound heterozygous genotype of the BBS2 gene in a 14-year-old girl and her 6-year-old sister who had complaints of early-onset low vision. Fundus images revealed retinitis pigmentosa-like changes, and full-field electroretinograms showed no amplitude for the rod or cone response in both patients. Interestingly, nystagmus was observed in the older sister. On physical examination, the sisters had moderate obesity without polydactyly, hypogonadism, or intellectual disability. Exome sequencing revealed a novel compound heterozygous genotype of BBS2 in the sisters, namely the paternally inherited NM_031885.5:c.534 + 1G > T variant and the maternally inherited NM_031885.5:c.700C > T (p.Arg234Ter) variant. Both variants were classified as pathogenic according to the American College of Medical Genetics and Genomics guidelines. This study provides useful information on the genotype-phenotype relationships of the BBS2 gene for genetic counseling and diagnosis.

PD1/PD-L1 checkpoint inhibitors are at the forefront of cancer immunotherapies. However, the overall response rate remains only 10–30%. Even among initial responders, drug resistance often occurs, which can lead to prolonged use of a futile therapy in the race with the fatal disease. It would be ideal to closely monitor key indicators of patients’ immune responsiveness, such as circulating PD-L1 levels. Traditional PD-L1 detection methods, such as ELISA, are limited in sensitivity and rely on core lab facilities, preventing their use for the regular monitoring. Electrochemical sensors exist as an attractive candidate for point-of-care tool, yet, streamlining multiple processes in a single platform remains a challenge. To overcome this challenge, this work integrated electrochemical sensor arrays into a digital microfluidic device to combine their distinct merits, so that soluble PD-L1 (sPD-L1) molecules can be rapidly detected in a programmed and automated manner. This new platform featured microscale electrochemical sensor arrays modified with electrically conductive 3D matrix, and can detect as low as 1 pg/mL sPD-L1 with high specificity. The sensors also have desired repeatability and can obtain reproducible results on different days. To demonstrate the functionality of the device to process more complex biofluids, we used the device to detect sPD-L1 molecules secreted by human breast cancer cell line in culture media directly and observed 2X increase in signal compared with control experiment. This novel platform holds promise for the close monitoring of sPD-L1 level in human physiological fluids to evaluate the efficacy of PD-1/PD-L1 immunotherapy.

Abstract Springtails (Collembola) inhabit soils from the Arctic to the Antarctic and comprise an estimated ~32% of all terrestrial arthropods on Earth. Here, we present a global, spatially-explicit database on springtail communities that includes 249,912 occurrences from 44,999 samples and 2,990 sites. These data are mainly raw sample-level records at the species level collected predominantly from private archives of the authors that were quality-controlled and taxonomically-standardised. Despite covering all continents, most of the sample-level data come from the European continent (82.5% of all samples) and represent four habitats: woodlands (57.4%), grasslands (14.0%), agrosystems (13.7%) and scrublands (9.0%). We included sampling by soil layers, and across seasons and years, representing temporal and spatial within-site variation in springtail communities. We also provided data use and sharing guidelines and R code to facilitate the use of the database by other researchers. This data paper describes a static version of the database at the publication date, but the database will be further expanded to include underrepresented regions and linked with trait data.

We adopted a simple and rapid measurement method to analyze the concentrations of monosaccharides (MCHO) and polysaccharides (PCHO) in carbohydrates, a subset of organic carbon found in size-fractionated atmospheric particles. Seasonal and source-related factors influenced carbohydrate concentrations, with total water-soluble carbohydrates (TCHO) accounting for approximately 23% of the water-soluble organic carbon (WSOC) in spring when biological activity was high. We observed that the mode of aerosol transport significantly influenced the particle size distribution of carbohydrates, with MCHO exhibiting relatively high concentrations in fine particles (1 μm). Moreover, our results revealed that MCHO and PCHO contributed 51% and 49%, respectively, to the TCHO concentration. This contribution varied by approximately ±19% depending on the season, suggesting the importance of both MCHO and PCHO. Additionally, through the combined use of principal component analysis (PCA) and positive matrix factorization (PMF), we determined that biomass burning accounts for 30% of the aerosol. Notably, biomass burning accounts for approximately 52% of the WSOC flux, with MCHO accounting for approximately 78% of the carbon from this source, indicating the substantial influence of biomass burning on aerosol composition. The average concentration of TCHO/WSOC in the atmosphere was approximately 18%, similar to the marine environment, reflecting the relationship between the biogeochemical cycles of the two environments. Finally, the fluxes of MCHO and PCHO were 1.10 and 5.28 mg C m−2 yr−1, respectively. We also found that the contribution of atmospheric deposition to marine primary productivity in winter was 15 times greater than that in summer, indicating that atmospheric deposition had a significant impact on marine ecosystems during nutrient-poor seasons. Additionally, we discovered that WSOC accounts for approximately 62% of the dissolved organic carbon (DOC) in the Min River, suggesting that atmospheric deposition could be a major source of organic carbon in the region.

The adoption of Open Educational Resources (OER) can, on the one hand, increase access and quality in higher education, but on the other hand it is raising concerns among universities and researchers about its economic sustainability. This is mainly because, unlike traditional online learning, in OER-based approaches learners do not have to pay to access learning resources, however the institution incurs costs for the production, maintenance and dissemination of OER. In this context, the United Nations Educational, Scientific and Cultural Organisation (UNESCO) has urgently called for more research on OER sustainability models in its 2019 OER recommendation. To contribute to a better understanding of this issue, this paper used the triangulation method to investigate the potential OER sustainability models that are currently implemented by universities, along with their challenges and possible developments. Through a comprehensive literature review and a 2-round Delphi method with thirty OER experts, ten OER sustainability models have been identified and analysed, where public and internal funding are the most established ones. The findings of this study could support organisations in developing their own OER sustainability strategy, facilitating OER adoption worldwide and therefore contributing to achieving the UN Sustainable Development Goals (SDGs).

Abstract Forest soils are a critical component of terrestrial ecosystems and host a large number of animal decomposer species. One diverse and abundant decomposer taxon is oribatid mites (Acari: Oribatida), whose species composition varies with forest type and tree species composition. We used functional traits that indicate different niche dimensions, to infer assembly processes of oribatid mite communities in monocultures and mixed forests of native and introduced tree species. We found that coexisting species differed more in the resource‐related niche dimension, i.e., reproductive mode and trophic guild, than in the morphological dimension, e.g., body length and width, sclerotization and concealability. These results suggest that both filtering and partitioning processes structure oribatid mite communities. In native European beech forests, but not in non‐native Douglas fir forests, oribatid mites were mainly structured by filtering processes acting via traits related both to environmental tolerance and to resources. Furthermore, oribatid mite trait diversity, but not phylogenetic diversity, differed significantly between monocultures and mixed forests, demonstrating that multidimensional diversity indices provide additional information on soil biodiversity. Overall, the study provides evidence that traits representing different niche dimensions need to be considered for understanding assembly processes in soil animal communities and thereby soil biodiversity.

IntroductionInflammatory bowel disease (IBD) is a chronic disease involving multiple genes, and the current available targeted drugs for IBD only deliver moderate efficacy. Whether there is a single gene that systematically regulates IBD is not yet known. MiR-146a plays a pivotal role in repression of innate immunity, but its function in the intestinal inflammation is sort of controversy, and the genetic regulatory networks regulated by miR-146a in IBD has not been revealed.MethodsRT-qPCR was employed to detect the expression of miR-146a in IBD patients and in a mouse IBD model induced by dextran sulfate sodium (DSS), and then we generated a miR-146a knock-out mouse line with C57/Bl6N background. The disease activity index was scored in DSS-treated miR-146a deficiency mice and their wild type (WT) littermates. Bulk RNA-sequencing, RT-qPCR and immunostaining were done to illustrate the downstream genetic regulatory networks of miR-146a in flamed colon. Finally, the modified miR-146a mimics were used to treat DSS-induced IBD in miR-146a knock-out and WT IBD mice.ResultsWe showed that the expression of miR-146a in the colon was elevated in dextran sulfate sodium (DSS)-induced IBD mice and patients with IBD. DSS induced dramatic body weight loss and more significant rectal bleeding, shorter colon length, and colitis in miR-146a knock-out mice than WT mice. The miR-146a mimics alleviated DSS-induced symptoms in both miR-146a-/- and WT mice. Further RNA sequencing illustrated that the deficiency of miR-146a de-repressed majority of DSS-induced IBD-related genes that cover multiple genetic regulatory networks in IBD, and supplementation with miR-146a mimics inhibited the expression of many IBD-related genes. Quantitative RT-PCR or immunostaining confirmed that Ccl3, Saa3, Csf3, Lcn2, Serpine1, Serpine2, MMP3, MMP8, MMP10, IL1A, IL1B, IL6, CXCL2, CXCL3, S100A8, S100A9, TRAF6, P65, p-P65, and IRAK1 were regulated by miR-146a in DSS induced IBD. Among them, MMP3, MMP10, IL6, IL1B, S100A8, S100A9, SERPINE1, CSF3, and IL1A were involved in the active stage of IBD in humans.DiscussionOur date demonstrated that miR-146a acts as a top regulator in C57/BL6N mice to systematically repress multiple genetic regulatory networks involved in immune response of intestine to environment factors, and combinatory treatment with miR-146a-5p and miR-146a-3p mimics attenuates DSS-induced IBD in mice through down-regulating multiple genetic regulatory networks which were increased in colon tissue from IBD patients. Our findings suggests that miR-146a is a top inhibitor of IBD, and that miR-146a-5p and miR-146a-3p mimics might be potential drug for IBD.