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The ectonucleotidases CD38 and CD39 have a critical regulatory effect on tumors and viral infections via the adenosine axis. Natural killer (NK) cells produce cytokines, induce cytotoxic responses against viral infection, and acquire immunoregulatory properties. However, the roles of CD38 and CD39 expressed NK cells in HIV disease require elucidation. Our study showed that the proportions of CD38+CD39+ NK cells in HIV-infected individuals were positively associated with HIV viral loads and negatively associated with the CD4+ T cell count. Furthermore, CD38+CD39+ NK cells expressed additional inhibitory receptors, TIM-3 and LAG-3, and produced more TGF-β. Moreover, autologous NK cells suppressed the proliferation of CD8+ T and CD4+ T cells of HIV-infected individuals, and inhibiting CD38 and CD39 on NK cells restored CD8+ T and CD4+ T cell proliferation in vitro. In conclusion, these data support a critical role for CD38 and CD39 on NK cells in HIV infection and targeting CD38 and CD39 on NK cells may be a potential therapeutic strategy against HIV infection.

Abstract Signals of radars with fixed, stagger and other conventional pulse repetition intervals (PRI) occupy a large proportion in most radar reconnaissance datasets. Automatic and accurate reconstruction of the PRI patterns of these radars is an important task in realizing intelligent processing of radar reconnaissance data. In order to address this problem, this article proposes an automatic method based on the extraction and extension of frequent differential time‐of‐arrival (DTOA) items, which can be combined with other pulse parameters such as pulse width. The values and ordering of the frequent items are determined to reconstruct a complete PRI cycle, and the radar pulses are deinterleaved at the same time as a by‐product. Compared with the commonly used one‐dimensional radar reconnaissance parameters such as framework PRI or typical PRI set, the reconstructed PRI pattern contains more information about radar operational modes and can be applied to realize online and parallel pulse deinterleaving and more accurate radar type classification.

In order to improve the measurement accuracy of near-bit apparent resistivity and its measurement range, this paper excites the underground transmitting antenna by a sinusoidal pulse-width modulated (SPWM) current excitation method, which can improve the response of the receiving antenna and circuit in the resistivity measurement system under the usual square wave excitation, thus improving the measurement accuracy of near-bit apparent resistivity. In this paper, the effect of square wave, SPWM wave and sine wave excitation on resistivity measurement was studied, and the modulation algorithm and hardware control are programmed by DSP (Digital Signal Processor), and the SPWM signal is output by full-bridge inverter circuit and tuned antenna. The indoor experimental results show that the near-bit apparent resistivity measurement method based on the SPWM wave pulse excitation can achieve the measurement in the range of formation equivalent resistor value of less than 600kΩ. There is a high trend matching between near-bit apparent resistivity LWD curve and RT resistivity curve of well completion electrical logging in field tests of formation resistivity less than 2000Ω·m, which proves that the method can improve the accuracy of near-bit apparent resistivity measurement. [ABSTRACT FROM AUTHOR]

Abstract Background T cell immunoglobulin and mucin domain-containing-3 (Tim-3) is a negative regulator expressed on T cells, and is also expressed on natural killer (NK) cells. The function of Tim-3 chiefly restricts IFNγ-production in T cells, however, the impact of Tim-3 on NK cell function has not been clearly elucidated. Results In this study, we demonstrated down-regulation of Tim-3 expression on NK cells while Tim-3 is upregulated on CD4+ T cells during HIV infection. Functional assays indicated that Tim-3 mediates suppression of CD107a degranulation in NK cells and CD4+ T cells, while it fails to inhibit the production of IFN-γ by NK cells. Analyses of downstream pathways using an antibody to block Tim-3 function demonstrated that Tim-3 can inhibit ERK and NFκB p65 signaling; however, it failed to suppress the NFAT pathway. Further, we found that the NFAT activity in NK cells was much higher than that in CD4+ T cells, indicating that NFAT pathway is important for promotion of IFN-γ production by NK cells. Conclusions Thus, our data show that the expression of Tim-3 on NK cells is insufficient to inhibit IFN-γ production. Collectively, our findings demonstrate a potential mechanism of Tim-3 regulation of NK cells and a target for HIV infection immunotherapy.

Abstract Background Recently, the relationship between thyroid hormones (THs) across the euthyroid ranges and metabolic syndrome (MetS) has been widely discussed. This study aimed to present specific cutoff values of THs to assess the association between THs and MetS in a euthyroid cohort. Methods Data of 2694 subjects, aged 18–80 years, who attended health examination in Xi’an Electric Power Central Hospital from April 2011 to December 2015 were collected and analyzed. The first cohort enrolled 929 participants (followed up by 2221 person-years totally) to assess correlations between serum thyrotropin (TSH), triiodothyronine (T3), thyroxine (T4) levels and MetS. The second cohort included 698 participants (followed up by 1709 person-years totally) to evaluate relationships between serum free triiodothyronine (FT3), free thyroxine (FT4) levels and MetS. MetS was defined according to the criteria of the American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI) scientific statements of 2009. Euthyroidism was defined as serum TSH, FT3 and FT4 levels within the reference ranges without taking any thyroid medication. Results The cutoff values for TSH, T3, T4, FT3 and FT4 were 2.0mIU/L, 1.9 nmol/L, 117 nmol/L, 4.3 pmol/L and 16 pmol/L, respectively. Participants were categorized into two groups according to cutoff values: the lower-THs group and the higher-THs group. There was no significant difference in the risk of MetS between two groups in TSH, T3, T4 and FT3. The incidence of MetS was significantly higher in lower-FT4 group than higher-FT4 group (1.00 vs 0.622 (0.458, 0.846), P = 0.002). The lower-FT4/higher-TSH group had the highest hazard ratios of MetS. (2.131vs 1.0 (1.380,3.291), P = 0.006). Conclusions Lower normal FT4 (FT4 ≤ 16.0 pmol/L) is an independent risk factor for MetS, and lower normal thyroid function (TSH > 2.0 mIU/L and FT4 ≤ 16.0 pmol/L) is associated with a higher risk of developing MetS.

Motivation High-throughput RNA sequencing has become indispensable for decoding gene activities, yet the challenge of reconstructing full-length transcripts persists. Traditional single-sample assemblers frequently produce fragmented transcripts, especially in single-cell RNA-seq data. While algorithms designed for assembling multiple samples exist, they encounter various limitations. Results We present Aletsch, a new assembler for multiple bulk or single-cell RNA-seq samples. Aletsch incorporates several algorithmic innovations, including a "bridging" system that can effectively integrate multiple samples to restore missed junctions in individual samples, and a new graph-decomposition algorithm that leverages "supporting" information across multiple samples to guide the decomposition of complex vertices. A standout feature of Aletsch is its application of a random forest model with 50 well-designed features for scoring transcripts. We demonstrate its robust adaptability across different chromosomes, datasets, and species. Our experiments, conducted on RNA-seq data from several protocols, firmly demonstrate Aletsch's significant outperformance over existing meta-assemblers. As an example, when measured with the partial area under the precision-recall curve (pAUC, constrained by precision), Aletsch surpasses the leading assemblers TransMeta by 22.9%–62.1% and PsiCLASS by 23.0%–175.5% on human datasets. Availability and implementation Aletsch is freely available at https://github.com/Shao-Group/aletsch. Scripts that reproduce the experimental results of this manuscript is available at https://github.com/Shao-Group/aletsch-test. [ABSTRACT FROM AUTHOR]

Motivation Many tasks in sequence analysis ask to identify biologically related sequences in a large set. The edit distance, being a sensible model for both evolution and sequencing error, is widely used in these tasks as a measure. The resulting computational problem—to recognize all pairs of sequences within a small edit distance—turns out to be exceedingly difficult, since the edit distance is known to be notoriously expensive to compute and that all-versus-all comparison is simply not acceptable with millions or billions of sequences. Among many attempts, we recently proposed the locality-sensitive bucketing (LSB) functions to meet this challenge. Formally, a (d 1 , d 2) -LSB function sends sequences into multiple buckets with the guarantee that pairs of sequences of edit distance at most d 1 can be found within a same bucket while those of edit distance at least d 2 do not share any. LSB functions generalize the locality-sensitive hashing (LSH) functions and admit favorable properties, with a notable highlight being that optimal LSB functions for certain (d 1 , d 2) exist. LSB functions hold the potential of solving above problems optimally, but the existence of LSB functions for more general (d 1 , d 2) remains unclear, let alone constructing them for practical use. Results In this work, we aim to utilize machine learning techniques to train LSB functions. With the development of a novel loss function and insights in the neural network structures that can potentially extend beyond this specific task, we obtained LSB functions that exhibit nearly perfect accuracy for certain (d 1 , d 2) ⁠ , matching our theoretical results, and high accuracy for many others. Comparing to the state-of-the-art LSH method Order Min Hash, the trained LSB functions achieve a 2- to 5-fold improvement on the sensitivity of recognizing similar sequences. An experiment on analyzing erroneous cell barcode data is also included to demonstrate the application of the trained LSB functions. Availability and implementation The code for the training process and the structure of trained models are freely available at https://github.com/Shao-Group/lsb-learn. [ABSTRACT FROM AUTHOR]

Context Hypothyroidism is often associated with cognitive and emotional dysregulation; however, the underlying neuropathological mechanisms remain elusive. Objective The study aimed to characterize abnormal alterations in hippocampal subfield volumes and functional connectivity (FC) in patients with subclinical hypothyroidism (SCH) and overt hypothyroidism (OH). Methods This cross-sectional observational study comprised 47 and 40 patients with newly diagnosed adult-onset primary SCH and OH, respectively, and 53 well-matched healthy controls (HCs). The demographics, clinical variables, and neuropsychological scale scores were collected. Next, the hippocampal subfield volumes and seed-based FC were compared between the groups. Finally, correlation analyses were performed. Results SCH and OH exhibited significant alterations in cognitive and emotional scale scores. Specifically, the volumes of the right granule cell molecular layer of the dentate gyrus (GC-ML-DG) head, cornu ammonis (CA) 4, and CA3 head were reduced in the SCH and OH groups. Moreover, the volumes of the right molecular layer head, CA1 body, left GC-ML-DG head, and CA4 head were lower in SCH. In addition, the hippocampal subfield volumes decreased more significantly in SCH than OH. The seed-based FC decreased in SCH but increased in OH compared with HCs. Correlation analyses revealed thyroid hormone was negatively correlated with FC values in hypothyroidism. Conclusion Patients with SCH and OH might be at risk of cognitive decline, anxiety, or depression, and exhibited alterations in volume and FC in specific hippocampal subfields. Furthermore, the reduction in volume was more pronounced in SCH. This study provides novel insights into the neuropathological mechanisms of brain impairment in hypothyroidism. [ABSTRACT FROM AUTHOR]

Electroporation techniques have emerged as attractive tools for intracellular delivery, rendering promising prospects towards clinical therapies. Transient disruption of membrane permeability is the critical process for efficient electroporation‐based cargo delivery. However, smart nanotools for precise characterization of transient membrane changes induced by strong electric pulses are extremely limited. Herein, multivalent membrane‐anchored fluorescent nanoprobes (MMFNPs) that take advantages of flexible functionalization and spatial arrangement of DNA frameworks are developed for in situ evaluation of electric field‐induced membrane permeability during reversible electroporation. Single‐molecule fluorescence imaging techniques are adopted to precisely verify the excellent analytical performance of the engineered MMFNPs. Benefited from tight membrane anchoring and sensitive adenosine triphosphate (ATP) profiling, varying degrees of membrane disturbances are visually exhibited under different intensities of the microsecond pulse electric field (µsPEF). Significantly, the dynamic process of membrane repair during reversible electroporation is well demonstrated via ATP fluctuations monitored by the designed MMFNPs. Furthermore, molecular dynamics (MD) simulations are performed for accurate verification of electroporation‐driven dynamic cargo entry via membrane nanopores. This work provides an avenue for effectively capturing transient fluctuations of membrane permeability under external stimuli, offering valuable guidance for developing efficient and safe electroporation‐driven delivery strategies for clinical diagnosis and therapeutics. [ABSTRACT FROM AUTHOR]

Accurate prediction of molecular properties is fundamental in drug discovery and development, providing crucial guidance for effective drug design. A critical factor in achieving accurate molecular property prediction lies in the appropriate representation of molecular structures. Presently, prevalent deep learning–based molecular representations rely on 2D structure information as the primary molecular representation, often overlooking essential three-dimensional (3D) conformational information due to the inherent limitations of 2D structures in conveying atomic spatial relationships. In this study, we propose employing the Gram matrix as a condensed representation of 3D molecular structures and for efficient pretraining objectives. Subsequently, we leverage this matrix to construct a novel molecular representation model, Pre-GTM, which inherently encapsulates 3D information. The model accurately predicts the 3D structure of a molecule by estimating the Gram matrix. Our findings demonstrate that Pre-GTM model outperforms the baseline Graphormer model and other pretrained models in the QM9 and MoleculeNet quantitative property prediction task. The integration of the Gram matrix as a condensed representation of 3D molecular structure, incorporated into the Pre-GTM model, opens up promising avenues for its potential application across various domains of molecular research, including drug design, materials science, and chemical engineering. [ABSTRACT FROM AUTHOR]

Understanding urban vertical structures, particularly building heights, is essential for examining the intricate interaction between humans and their environment. Such datasets are indispensable for a variety of applications, including climate modeling, energy consumption analysis, and socioeconomic activities. Despite the importance of this information, previous studies have primarily focused on estimating building heights regionally on a grid scale, often resulting in datasets with limited coverage or spatial resolution. This limitation hampers comprehensive global analyses and the ability to generate actionable insights on finer scales. In this study, we developed a global building height map (3D-GloBFP) at a building footprint scale by leveraging Earth Observation (EO) datasets and advanced machine learning techniques. Our approach integrated multisource remote sensing features and building morphology features to develop height estimation models using the eXtreme Gradient Boosting (XGBoost) regression method across diverse global regions. This methodology allowed us to estimate the heights of individual buildings worldwide, culminating in the creation of the first global three-dimensional (3-D) building footprints (3D-GloBFP). Our evaluation results show that the height estimation models perform exceptionally well on a worldwide scale, with R 2 ranging from 0.66 to 0.96 and root mean square errors (RMSEs) ranging from 1.9 m to 14.6 m across 33 subregions. Comparisons with other datasets demonstrate that our 3D-GloBFP closely matches the distribution and spatial pattern of reference heights. Our derived 3-D global building footprint map shows a distinct spatial pattern of building heights across regions, countries, and cities, with building heights gradually decreasing from the city center to the surrounding rural areas. Furthermore, our findings indicate the disparities in built-up infrastructure (i.e., building volume) across different countries and cities. China is the country with the most intensive total built-up infrastructure (5.28×1011 m3, accounting for 23.9 % of the global total), followed by the United States (3.90×1011 m3, accounting for 17.6 % of the global total). Shanghai has the largest volume of built-up infrastructure (2.1×1010 m3) of all representative cities. The derived building-footprint scale height map (3D-GloBFP) reveals the significant heterogeneity of urban built-up environments, providing valuable insights for studies in urban socioeconomic dynamics and climatology. The 3D-GloBFP dataset is available at https://doi.org/10.5281/zenodo.11319913 (Building height of the Americas, Africa, and Oceania in 3D-GloBFP) (Che et al., 2024a), https://doi.org/10.5281/zenodo.11397015 (Building height of Asia in 3D-GloBFP) (Che et al., 2024b), and https://doi.org/10.5281/zenodo.11391077 (Building height of Europe in 3D-GloBFP) (Che et al., 2024c). [ABSTRACT FROM AUTHOR]

Highly cross‐linked thermosets possess superior mechanical properties and have found broad applications in engineering. However, due to the dense cross‐links, it is extremely challenging to recycle highly cross‐linked thermosets, causing serious environmental and sustainable concerns. Herein, a mechanochemical recycling strategy is proposed for highly cross‐linked thermosets via the synergy of mechanics and chemistry, which is economic‐friendly and pollution‐free. To demonstrate the strategy, diverse metal‐complex catalysts are employed to recycle highly cross‐linked epoxy incorporated with switchable covalent bonds at certain pressure, temperature, and time. The effect of each catalyst on the efficiency of recycling is evaluated, which follows a descending order: Zr4+ > Mn3+ > Co3+ > Fe3+ > Co2+ > Zn2+ > OTi4+ > Ni2+. The results show that the mechanical properties, such as Young's modulus, ultimate strength, peak strain, impact strength, flexural modulus and strength, as well as thermal stability of the recycled samples are almost identical to those of as‐synthesized ones. The effectiveness of the method is further confirmed via micromorphology. [ABSTRACT FROM AUTHOR]

Engineering projects necessitate efficient and resilient collaboration. Enhancing collaboration requires designing and optimizing information interactions. Current methodologies lack a processual and relational lens; also, they seldom emphasize the significance of information. This study focused on information collaboration (IC) in engineering projects. We devised an integrated framework with an information perspective and a network perspective. The framework comprises (1) a two-layer information collaboration network model, integrating information demands and flows; (2) network analysis across different project levels, detecting stakeholder roles in collaboration, revealing unevenly distributed collaboration configurations, and presenting overall collaboration patterns; and (3) a novel assessment method for collaboration performance considering the efficiency and resilience of IC. The framework's practicality was validated through a large-scale international airport project. It offers strategies for enhancing collaboration via network interventions and information optimization. Findings promote the recognition of collaboration, clarify the mechanism between information demands and flows, and improve collaboration performance. It also paves the way for project resilience management. [ABSTRACT FROM AUTHOR]

Background: To investigate the effect of flavaspidic acid BB (BB) on biofilms and quorumsensing-related genes of drug-resistant Staphylococcus epidermidis (SE) and to provideatheoretical basis for the development of BB as a new type of quorumsensing inhibitor. Methods: The microdilution method was applied to screen 15 clinical isolates of S. epidermidis for drug-resistant S. epidermidis to be used as the test strain. The effects of BBonthe biofilms of drug-resistant S. epidermidis at different growth stages were studied usingthecell counting kit-8 assay and scanning electron microscopy. The gene expression of sigB, sarA, and luxS, regulators involved in quorum sensing of biofilm formation, was measuredby PCR. Results: The minimum inhibitory concentrations of BB against 15 clinical strains of S. epidermidis ranged 11.67–66.67 µg/mL. BB significantly inhibited biofilmformationbydrug-resistant SE06 in the aggregation and maturation stages, with an activity superior tothose of mupirocin and fusidic acid (P < 0.05). At 40 µg/mL, BB reduced the secretionof extracellular polymers and promoted the disruption of biofilm structure. At 80 µg/mL, BBspecifically interfered with the quorum sensing system of drug-resistant SE06bydownregulating sarA and luxS, thereby inhibiting this microbe’s biofilmformation. Conclusion: BB exhibited strong inhibitory activity against SE06 by suppressing biofilmformation and downregulating quorum sensing-related genes and was identified as anewpotential quorum sensing inhibitor against S. epidermidis. [ABSTRACT FROM AUTHOR]

Layered double hydroxides (LDHs) are widely studied to enhance corrosion resistance and biocompatibility of Mg alloys, which are promising bone implants. However, the influence of LDH coating on the osteointegration of Mg implants lacks of a systematic study. In this work, Mg-Al LDH coating was prepared on pure Mg via hydrothermal treatment. The as-prepared Mg-Al LDH coated Mg exhibited better in vitro and in vivo corrosion resistance than bare Mg and Mg(OH)2 coated Mg. In vitro culture of mouse osteoblast cell line (MC3T3-E1) suggested that Mg-Al LDH coated Mg was more favorable for its osteogenic differentiation. In vitro culture of HUVECs revealed that cells cultured in the extract of Mg-Al LDH coated Mg showed superior angiogenic behaviors. More importantly, the immune response of Mg-Al LDH coated Mg was studied by in vitro culturing murine-derived macrophage cell line (RAW264.7). The results verified that Mg-Al LDH coated Mg could induce macrophage polarize to M2 phenotype (anti-inflammatory). Furthermore, the secreted factor in the macrophage-conditioned culture medium of Mg-Al LDH group was more suitable for the bone differentiation of rat bone marrow stem cells (rBMSCs) and the angiogenic behavior of human umbilical vein endothelial cells (HUVECs). Finally, the result of femoral implantation suggested that Mg-Al LDH coated Mg exhibited better osteointegration than bare Mg and Mg(OH)2 coated Mg. With favorable in vitro and in vivo performances, Mg-Al LDH is promising as protective coating on Mg for orthopedic applications.

Soft tissue sealing around implants acts as a barrier between the alveolar bone and oral environment, protecting implants from the invasion of bacteria or external stimuli. In this work, magnesium (Mg) and zinc (Zn) are introduced into titanium by plasma immersed ion implantation technology, and their effects on the behaviors of human gingival fibroblasts (HGFs) as well as the underlying mechanisms are investigated. Surface characterization confirms Mg and Zn exist on the surface in metallic and oxidized states. Contact angle test suggests that surface wettability of titanium changes after ion implantation and thus influences protein adsorption of surfaces. In vitro studies disclose that HGFs on Mg ion-implanted samples exhibit better adhesion and migration while cells on Zn ion-implanted samples have higher proliferation rate and amounts. The results of immunofluorescence staining and real-time reverse-transcriptase polymerase chain reaction (RT-PCR) suggest that Mg mainly regulates the motility and adhesion of HGFs through activating the MAPK signal pathway whereas Zn influences HGFs proliferation by triggering the TGF-β signal pathway. The synergistic effect of Mg and Zn ions ensure that HGFs cultured on co-implanted samples possessed both high proliferation rate and motility, which are critical to soft tissue sealing of implants.

Type 50 early infantile epileptic encephalopathy, or EIEE-50 for short, is an autosomal recessive genetic disorder resulting from CAD mutations. So far, little has been reported on the disease. In this article, we will discuss the case of a male infant who is 8 years and 5 months old. A whole-exome sequencing of the boy revealed CAD compound heterozygous mutations. He suffered from global developmental delay and regression, refractory epilepsy, and anemia. After his diagnosis, we used uridine treatment and gained encouraging results. In this article, we will analyze our case studies in the context of the literature, so as to improve pediatricians' understanding of the disease.

Summary: Myeloid-derived suppressor cells (MDSCs) and tumor-associated macrophages (TAMs) play critical roles in tumorigenesis. However, the mechanisms underlying MDSC and TAM development and function remain unclear. In this study, we find that myeloid-specific activation of Notch/RBP-J signaling downregulates lactate transporter MCT2 transcription via its downstream molecule Hes1, leading to reduced intracellular lactate levels, blunted granulocytic MDSC (G-MDSC) differentiation, and enhanced TAM maturation. We identify c-Jun as a novel intracellular sensor of lactate in myeloid cells using liquid-chromatography-mass spectrometry (LC-MS) followed by CRISPR-Cas9-mediated gene disruption. Meanwhile, lactate interacts with c-Jun to protect from FBW7 ubiquitin-ligase-mediated degradation. Activation of Notch signaling and blockade of lactate import repress tumor progression by remodeling myeloid development. Consistently, the relationship between the Notch-MCT2/lactate-c-Jun axis in myeloid cells and tumorigenesis is also confirmed in clinical lung cancer biopsies. Taken together, our current study shows that lactate metabolism regulated by activated Notch signaling might participate in MDSC differentiation and TAM maturation.