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Abstract Most aftershocks occur in areas experiencing large co‐seismic stress changes, yet some occur long after the mainshock in remote lightly stressed regions. The triggering mechanism of these remote delayed aftershocks is not well understood. Here, we study aftershocks occurring in the Dead Sea (DS) area following the 2023 Mw7.8 and Mw7.6 Kahramanmaraş earthquakes. Most aftershocks cluster along previously quiescent structures off‐ the main DS fault strand. Visual inspection disclosed three aftershocks instantaneously triggered by the Mw7.6 in the northern DS basin, and match‐filtering revealed a delayed aftershock. Waveform similarity and temporal clustering suggest the northern DS aftershocks re‐rupture a stick‐slip patch loaded by surrounding creep. Velocity‐gradient seismograms show the Mw7.6 exerted larger transient stresses than the Mw7.8, which may explain triggering by the Mw7.6, but not by the Mw7.8. This account of instantaneously triggered repeaters underscores the role of interactions between aseismic and seismic slip in remote triggering.

Abstract The use of weather radars to detect and distinguish between different biological patterns greatly improves our understanding of aeroecology and its consequences for our lives. Importantly, it allows us to quantify passerine bird migration at different scales. Yet, no algorithm to detect soaring bird flocks in weather radar is available, precluding our ability to study this type of migration over large spatial scales. We developed the first automatic algorithm for detecting the migration of flocks of soaring birds, an important bio‐flow phenomenon involving many millions of birds that travel across large spatial extents, with implications for risk of bird‐aircraft collisions. The algorithm was developed with a deep learning network for semantic segmentation using U‐Net architecture. We tested several models with different weather radar products and with image sequences for flock movement identification. The best model includes the radial velocity product and a sequence of two previous images. It identifies 93% of soaring bird flocks that were tagged by a human on the radar image, with a false discovery of less than 20%. Large birds such as those detected by the algorithm pose a serious risk for flight safety of civilian and military transportation and therefore the application of this algorithm can substantially reduce bird‐strikes, leading to reduced financial losses and threats to human lives. In addition, it can help overcome one of the main challenges in the study of bird migration by automatically and continuously detecting flocks of large birds over wide spatial scales without the need to equip the birds with tracking devices, unravelling the abundance, timing, spatial flyways, seasonal trends and influences of environmental conditions on the migration of bird flocks.

Abstract Ionizable lipid‐based nanoparticles (LNPs) are the most advanced non‐viral drug delivery systems for RNA therapeutics and vaccines. However, cell type‐specific, extrahepatic mRNA delivery is still a major hurdle, hampering the development of novel therapeutic modalities. Herein, a novel ionizable lipid library is synthesized by modifying hydrophobic tail chains and linkers. Combined with other helper lipids and utilizing a microfluidic mixing approach, stable LNPs are formed. Using Luciferase‐mRNA, mCherry mRNA, and Cre mRNA together with a TdTomato animal model, superior lipids forming LNPs for potent cell‐type specific mRNA delivery are identified. In vitro assays concluded that combining branched ester tail chains with hydroxylamine linker negatively affects mRNA delivery efficiency. In vivo studies identify Lipid 23 as a liver‐trophic, superior mRNA delivery lipid and Lipid 16 as a potent cell type‐specific ionizable lipid for the CD11bhi macrophage population without an additional targeting moiety. Finally, in vivo mRNA delivery efficiency and toxicity of these LNPs are compared with SM‐102‐based LNP (Moderna's LNP formulation) and are shown to be cell‐specific compared to SM‐102‐based LNPs. Overall, this study suggests that a structural combination of tail and linker can drive a novel functionality of LNPs in vivo.

Abstract Multiple myeloma (MM) is a cancer of differentiated plasma cells that occurs in the bone marrow (BM). Despite the recent advancements in drug development, most patients with MM eventually relapse and the disease remains incurable. RNA therapy delivered via lipid nanoparticles (LNPs) has the potential to be a promising cancer treatment, however, its clinical implementation is limited due to inefficient delivery to non‐hepatic tissues. Here, targeted (t)LNPs designed for delivery of RNA payload to MM cells are presented. The tLNPs consist of a novel ionizable lipid and are coated with an anti‐CD38 antibody (αCD38‐tLNPs). To explore their therapeutic potential, it is demonstrated that LNPs encapsulating small interference RNA (siRNA) against cytoskeleton‐associated protein 5 (CKAP5) lead to a ≈90% decrease in cell viability of MM cells in vitro. Next, a new xenograft MM mouse model is employed, which clinically resembles the human disease and demonstrates efficient homing of MM cells to the BM. Specific delivery of αCD38‐tLNPs to BM‐residing and disseminated MM cells and the improvement in therapeutic outcome of MM‐bearing mice treated with αCD38‐tLNPs‐siRNA‐CKAP5 are shown. These results underscore the potential of RNA therapeutics for treatment of MM and the importance of developing effective targeted delivery systems and reliable preclinical models.

Abstract Background Juvenile myoclonic epilepsy (JME) is characterized by generalized seizures. Nearly 30% of JME patients are drug‐resistant (DR‐JME), indicating a widespread cortical dysfunction. Walking is an important function that necessitates orchestrated coordination of frontocentral cortical regions. However, gait alterations in JME have been scarcely investigated. Our aim was to assess changes in gait and motor‐evoked responses in DR‐JME patients. Methods Twenty‐nine subjects (11 JME drug‐responder, 8 DR‐JME, and 10 healthy controls) underwent a gait analyses during usual walking and dual‐task walking. Later, subjects underwent 64‐channel EEG recordings while performing a simple motor task. We calculated the motor‐evoked current source densities (CSD) at a priori chosen cortical regions. Gait and CSD measures were compared between groups and tasks using mixed model analysis. Results DR‐JME patients demonstrated an altered gait pattern that included slower gait speed (p = .018), reduced cadence (p = .003), and smaller arm‐swing amplitude (p = .011). The DR‐JME group showed higher motor‐evoked CSD in the postcentral gyri compared to responders (p = .049) and both JME groups showed higher CSD in the superior frontal gyri compared to healthy controls (p |–0.494|, p

Abstract The intestinal microbiome has emerged as an important component involved in various diseases. Therefore, the interest in understanding the factors shaping its composition is growing. The gut microbiome, often defined as a complex trait, contains diverse components and its properties are determined by a combination of external and internal effects. Although much effort has been invested so far, it is still difficult to evaluate the extent to which human genetics shape the composition of the gut microbiota. However, in mouse studies, where the environmental factors are better controlled, the effect of the genetic background was significant. The purpose of this paper is to provide a current assessment of the role of human host genetics in shaping the gut microbiome composition. Despite the inconsistency of the reported results, it can be estimated that the genetic factor affects a portion of the microbiome. However, this effect is currently lower than the initial estimates, and it is difficult to separate the genetic influence from the environmental effect. Additionally, despite the differences between the microbial composition of humans and mice, results from mouse models can strengthen our knowledge of host genetics underlying the human gut microbial variation.

A new technique for sperm analysis is presented, measuring DNA fragmentation, morphology with virtual staining, and motility, all three criteria on the same individual unstained live cell. The method relies on quantitative stain‐free interferometric imaging, providing unique topographic structural and content maps of the cell, becoming available for the first time for clinical use, together with deep‐learning frameworks and least‐squares linear approximation. In the common clinical practice, only motility evaluation can be carried out on live human cells, while full morphological evaluation and DNA fragmentation assays require different staining protocols, and therefore cannot be performed on the same cell, resulting in inconsistencies in fertility evaluation. A clinic‐ready interferometric module is used to acquire dynamic sperm cells without chemical staining, together with deep learning to evaluate all three scores per cell with accuracy of 93.1%, 88%, and 90% for morphology, motility, and DNA fragmentation, respectively. It is shown that the expected number of cells that pass all three criteria based on the current evaluations performed separately does not correspond with the number of cells that pass all criteria, demonstrating the importance of the suggested method. The proposed stain‐free evaluation method is expected to decrease uncertainty in infertility diagnosis, increasing treatment success rates.

Abstract Introduction We examined relationships of body mass index (BMI) with cognition in middle‐aged adults at Alzheimer's disease (AD) risk due to parental family history. Methods Participants are offspring of AD patients from the Israel Registry of Alzheimer's Prevention (N = 271). Linear regressions assessed associations of BMI and cognition, and whether associations differed by maternal/paternal history. Analyses of covariance examined associations of long‐term trajectories of BMI with cognition. Results Higher BMI was associated with worse language (P = .045). Interactions of BMI with parental history were significant for episodic memory (P = .023), language (p = .027), working memory (P = .006), global cognition (P = .008); associations were stronger among participants with maternal history. Interactions of BMI trajectories with parental history were significant for episodic memory (P = .017), language (P = .013), working memory (P = .001), global cognition (P = .005), with stronger associations for maternal history. Discussion Higher BMI and overweight/obese trajectories were associated with poorer cognition in adults with maternal history of AD, but not those with paternal history.