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Genetic diseases of blood cells are prime candidates for treatment through ex vivo gene editing of CD34+ hematopoietic stem/progenitor cells (HSPCs), and a variety of technologies have been proposed to treat these disorders. Sickle cell disease (SCD) is a recessive genetic disorder caused by a single-nucleotide polymorphism in the β-globin gene (HBB). Sickle hemoglobin damages erythrocytes, causing vasoocclusion, severe pain, progressive organ damage, and premature death. We optimize design and delivery parameters of a ribonucleoprotein (RNP) complex comprising Cas9 protein and unmodified single guide RNA, together with a single-stranded DNA oligonucleotide donor (ssODN), to enable efficient replacement of the SCD mutation in human HSPCs. Corrected HSPCs from SCD patients produced less sickle hemoglobin RNA and protein and correspondingly increased wild-type hemoglobin when differentiated into erythroblasts. When engrafted into immunocompromised mice, ex vivo treated human HSPCs maintain SCD gene edits throughout 16 weeks at a level likely to have clinical benefit. These results demonstrate that an accessible approach combining Cas9 RNP with an ssODN can mediate efficient HSPC genome editing, enables investigator-led exploration of gene editing reagents in primary hematopoietic stem cells, and suggests a path toward the development of new gene editing treatments for SCD and other hematopoietic diseases.

Myeloproliferative neoplasms (MPNs) are associated with significant alterations in the bone marrow microenvironment that include decreased expression of key niche factors and myelofibrosis. Here, we explored the contribution of TGF-[beta] to these alterations by abrogating TGF-[beta] signaling in bone marrow mesenchymal stromal cells. Loss of TGF-[beta] signaling in Osx-Cre-targeted MSCs prevented the development of myelofibrosis in both [MPL.sup.W515L] and [Jak2.sup.V617F] models of MPNs. In contrast, despite the absence of myelofibrosis, loss of TGF-[beta] signaling in mesenchymal stromal cells did not rescue the defective hematopoietic niche induced by [MPL.sup.W515L], as evidenced by decreased bone marrow cellularity, hematopoietic stem/ progenitor cell number, and Cxcl12 and Kitlg expression, and the presence of splenic extramedullary hematopoiesis. Induction of myelofibrosis by [MPL.sup.W515L] was intact in Osx-Cre [Smad4.sup.fl/fl] recipients, demonstrating that SMAD4-independent TGF-[beta] signaling mediates the myelofibrosis phenotype. Indeed, treatment with a c-Jun N-terminal kinase (JNK) inhibitor prevented the development of myelofibrosis induced by [MPL.sup.W515L]. Together, these data show that JNK-dependent TGF-[beta] signaling in mesenchymal stromal cells is responsible for the development of myelofibrosis but not hematopoietic niche disruption in MPNs, suggesting that the signals that regulate niche gene expression in bone marrow mesenchymal stromal cells are distinct from those that induce a fibrogenic program., Introduction The bone marrow provides a specialized microenvironment that supports hematopoiesis. Hematopoietic niches in the bone marrow are dependent, in part, on the constitutive production of certain cytokines and chemokines [...]

Water use efficiency (WUE) is a key indicator for predicting the impacts of climate change on ecosystem carbon and water cycles. Most studies have explored the changes in the response environment of WUE at a particular scale. Few studies have examined how WUE responds to environments at multiple scales, thus limiting our in-depth understanding of the cross-scale carbon and water cycles. In this study, we measured photosynthesis and transpiration in situ periodically and continuously from June to October 2022 in a community dominated by Artemisia ordosica in Mu Us Sandy Land, and analyzed the seasonal variations in WUE at leaf, canopy, and ecosystem scales. The results showed there were significant seasonal variations in leaf water use efficiency (WUEL), canopy water use efficiency (WUET), and ecosystem water use efficiency (WUEE). WUEL was large in June and small in both August and September, ranging from 0.73-2.98 µmol • mmol-1. Both WUET and WUEE were lowest in June and highest in July and August, ranging from 0.10-7.00 and 0.06-6.25 µmol • mmol-1. WUEL was significantly negatively correlated with stomatal conductance. WUET was significantly positively correlated with canopy conductance and soil water content, and negatively correlated with vapor pressure deficit (VPD). There was a significant positive correlation between WUEE and soil water content (SWC10) in 10 cm soil depth. The structural equation model showed that SWC10 and air temperature affected net photosynthetic rate and transpiration rate by modifying stomatal conductance, and thus affecting WUEL. VPD and SWC10 affected WUET by altering transpiration. SWC10, air temperature, and VPD affected WUEE by regulating ecosystem gross primary productivity. The modelling of carbon and water cycles should thoroughly consider the path and intensity of the effect of environmental factors on WUE at multiple scales. [ABSTRACT FROM AUTHOR]

In the current era of urban construction, smart city management, and digital twinning, three-dimensional reconstruction of urban buildings is particularly important. Traditional methods have limitations in reconstructing complex geometric scenes, while new methods such as Nerf focus on using implicit MLP to represent the geometric space of the model, but suffer from slow training and rendering speeds. To address this issue, this paper proposes the use of 3D Gaussian scatter points for three-dimensional reconstruction of urban buildings, improving training speed and reconstruction quality through optimized and accelerated rendering algorithms. This method demonstrates high efficiency and editability, providing a new solution for urban building reconstruction. [ABSTRACT FROM AUTHOR]

Panoramic images, prized for their capacity to capture a comprehensive 360-degree field of view, find extensive applications across various domains. However, the challenge arises when attempting to seamlessly stitch together images captured by multiple cameras onto a spherical surface, particularly in cases where the cameras lack concentric alignment. To mitigate this misalignment issue, our paper introduces a novel method that integrates depth information into panoramic image stitching, aiming to enhance registration accuracy and seamline detection. The proposed method encompasses two pivotal steps. Firstly, depth information is employed to rectify the image's placement on the panoramic sphere, facilitating a two-dimensional registration process. This initial step targets the elimination of misalignment problems between images while preserving image clarity. Subsequently, depth information is seamlessly integrated into the smoothing term of the Markov random field energy function to guide seamline detection. Leveraging depth information aids in circumventing foreground obstacles and directs the search through spatially smooth areas, thereby reducing the likelihood of misalignment issues. Experimental results substantiate the effectiveness of employing depth information for image correction on the spherical surface, especially in scenarios where cameras approximate concentric alignment. Furthermore, the integration of depth information into the stitching network construction markedly diminishes misalignment, leading to a notable improvement in panoramic image quality. This signifies a crucial advancement in the domain of panoramic image stitching from an academic perspective. [ABSTRACT FROM AUTHOR]

Objective Accumulating evidence from microbial studies have highlighted the modulatory roles of intestinal microbes in numerous human diseases, however, the shared microbial signatures across different diseases remain relatively unclear. Methods To consolidate existing knowledge across multiple studies, we performed meta-analyses of 17 disease types, covering 34 case–control datasets of 16S rRNA sequencing data, to identify shared alterations among different diseases. Furthermore, the impact of a microbial species, Lactobacillus salivarius , was established in a dextran sodium sulphate–induced colitis model and a collagen type II–induced arthritis mouse model. Results Microbial alterations among autoimmune diseases were substantially more consistent compared with that of other diseases (cancer, metabolic disease and nervous system disease), with microbial signatures exhibiting notable discriminative power for disease prediction. Autoimmune diseases were characterized by the enrichment of Enterococcus , Veillonella , Streptococcus and Lactobacillus and the depletion of Ruminococcus , Gemmiger , Oscillibacter , Faecalibacterium , Lachnospiracea incertae sedis , Anaerostipes , Coprococcus , Alistipes , Roseburia , Bilophila , Barnesiella , Dorea , Ruminococcus2 , Butyricicoccus , Phascolarctobacterium , Parabacteroides and Odoribacter , among others. Functional investigation of L. salivarius , whose genus was commonly enriched in numerous autoimmune diseases, demonstrated protective roles in two separate inflammatory mouse models. Conclusion Our study highlights a strong link between autoimmune diseases and the gut microbiota, with notably consistent microbial alterations compared with that of other diseases, indicating that therapeutic strategies that target the gut microbiome may be transferable across different autoimmune diseases. Functional validation of L. salivarius highlighted that bacterial genera associated with disease may not always be antagonistic, but may represent protective or adaptive responses to disease. [ABSTRACT FROM AUTHOR]

Video lectures are indispensable components of current online learning platforms. They play critical roles in shaping learners' responses and learning performance. This research intends to synthesize the findings relevant to the effects of video lecture design on learners in online learning. It identified the key elements of video lecture design and revealed their impacts on learners' responses and learning performance by conducting a systematic review. Based on 73 peer-reviewed journal papers extracted and selected from the Web of Science (WOS) core collections database, this research illustrated the landscape of the literature by publication year, journal source, citations, and keyword co-occurrence. It also identified three themes in the literature, such as instructor presence, instructor characteristics, and content presentation, and summarized the key findings for each theme. This research contributes to the online learning literature by revealing the current status of scholarly works relevant to video lecture design and proposes an agenda for future research in this emerging field. Meanwhile, it offers practitioners the synthesized findings in the academic investigations on video lecture design in online learning. [ABSTRACT FROM AUTHOR]

The measurement of hemoglobin is a vital index for diagnosing and monitoring diseases in clinical practice. At present, solutions need to be found for the soreness, high risk of infection, and inconvenient operation associated with invasive detection methods. This paper proposes a method for non-invasively detecting hemoglobin levels based on multi-wavelength photoplethysmography (PPG) signals. AFE4490 and TMUX1109 were used to implement the low-cost collection of an eight-LED transmissive PPG signal. We used seven regular LEDs and one broadband LED (Osram SFH4737) as light sources. Additionally, a finger clip integrating multiple sensors was designed and manufactured via 3D printing to simultaneously monitor the LED–sensor distance and the pressure from the tester's finger during PPG signal acquisition. We used a method to extract features from PPG signals using a sliding-window's variance and an evaluation metric for PPG signals based on the AdaCost classification. Data were gathered from 56 participants from the Nephrology department, including 16 anemic patients. Pearson correlation analysis was conducted on the collected data to remove any data with a weak correlation. The advantage of using a broadband LED as a light source was also demonstrated. Several non-invasive hemoglobin regression models were created by applying AdaBoost, BPNN, and Random Forest models. The study's results indicate that the AdaBoost model produced the best performance, with a mean absolute error (MAE) of 2.67 g/L and a correlation coefficient (R2) of 0.91 The study results show that the device we designed and manufactured can achieve effective non-invasive hemoglobin detection and represents a new methodological approach to obtaining measurements that can be applied in a clinical setting. [ABSTRACT FROM AUTHOR]