Heliyon. 2024 Feb 7;10(4):e24775. doi: 10.1016/j.heliyon.2024.e24775. eCollection 2024 Feb 29.

ABSTRACT

In microbiome studies, the diversity and types of microbes have been extensively explored; however, the significance of microbial ecology is equally paramount. The comprehension of metabolic interactions among the wide array of microorganisms in the lung microbiota is indispensable for understanding chronic pulmonary disease and for the development of potent treatments. In this investigation, metabolic networks were simulated, and ecological theory was employed to assess the diagnosis of COPD, subsequently suggesting innovative treatment strategies for COPD exacerbation. Lung sputum 16S rRNA paired-end data from 112 COPD patients were utilized, and a supervised machine-learning algorithm was applied to identify taxa associated with sex and mortality. Subsequently, an OTU table with Greengenes 99 % dataset was generated. Finally, the interactions between bacterial species were analyzed using a simulated metabolic network. A total of 1781 OTUs and 1740 bacteria at the genus level were identified. We employed an additional dataset to validate our analyses. Notably, among the more abundant genera, Pseudomonas was detected in females, while Lactobacillus was detected in males. Additionally, a decrease in bacterial diversity was observed during COPD exacerbation, and mortality was associated with the high abundance of the Staphylococcus and Pseudomonas genera. Moreover, an increase in Proteobacteria abundance was observed during COPD exacerbations. In contrast, COPD patients exhibited decreased levels of Firmicutes and Bacteroidetes. Significant connections between microbial ecology and bacterial diversity in COPD patients were discovered, highlighting the critical role of microbial ecology in the understanding of COPD. Through the simulation of metabolic interactions among bacteria, the observed dysbiosis in COPD was elucidated. Furthermore, the prominence of anaerobic bacteria in COPD patients was revealed to be influenced by parasitic relationships. These findings have the potential to contribute to improved clinical management strategies for COPD patients.

PMID:38370212 | PMC:PMC10869780 | DOI:10.1016/j.heliyon.2024.e24775

Am J Primatol. 2024 Feb 18:e23607. doi: 10.1002/ajp.23607. Online ahead of print.

ABSTRACT

Rapid facial mimicry (RFM), the rapid and automatic replication of facial expression perceived, is considered a basic form of empathy and was investigated mainly during play. RFM occurs in Catarrhini (Old World primates), but it is not still demonstrated in Platyrrhini (New World primates). For this reason, we collected video data on playful interactions (Nplay_interactions = 149) in three species of spider monkeys (Ateles fusciceps-N = 11, Ateles hybridus-N = 14, and Ateles paniscus-N = 6) housed at La Vallée des Singes and the ZooParc de Beauval (France). For the first time, we demonstrated the occurrence of RFM in Platyrrhini (analyzing 175 events). Players' sex, age, species, relationship quality, and kinship did not modulate RFM probably due to the species' complex fission-fusion dynamics and flexible interindividual social relationships. Compared to the absence of any playful expressions or the presence of only not replicated play face, RFM prolonged the session duration and was sequentially associated with more types of more intense offensive playful patterns (patterns aimed at attacking/pursuing the playmate). We proposed that RFM may favor synchronization and context sharing between players, thus decreasing the risk of behavior misinterpretation while simultaneously fostering a more competitive nature of play. In conclusion, this study stimulates additional research on the evolutionary origins of motor mimicry in primates, possibly dating back to before the divergence of New and Old World monkeys. Furthermore, it also points toward the possibility that RFM may not always lead to cooperation but also to competition, depending on the context and species' social and cognitive features.

PMID:38369692 | DOI:10.1002/ajp.23607

Hum Genet. 2024 Feb 18. doi: 10.1007/s00439-024-02641-w. Online ahead of print.

ABSTRACT

Cisplatin-induced acute kidney injury (CP-AKI) is a common complication in cancer patients. Although ferroptosis is believed to contribute to the progression of CP-AKI, its mechanisms remain incompletely understood. In this study, after initially processed individual omics datasets, we integrated multi-omics data to construct a ferroptosis network in the kidney, resulting in the identification of the key driver TACSTD2. In vitro and in vivo results showed that TACSTD2 was notably upregulated in cisplatin-treated kidneys and BUMPT cells. Overexpression of TACSTD2 accelerated ferroptosis, while its gene disruption decelerated ferroptosis, likely mediated by its potential downstream targets HMGB1, IRF6, and LCN2. Drug prediction and molecular docking were further used to propose that drugs targeting TACSTD2 may have therapeutic potential in CP-AKI, such as parthenolide, progesterone, premarin, estradiol and rosiglitazone. Our findings suggest a significant association between ferroptosis and the development of CP-AKI, with TACSTD2 playing a crucial role in modulating ferroptosis, which provides novel perspectives on the pathogenesis and treatment of CP-AKI.

PMID:38369676 | DOI:10.1007/s00439-024-02641-w

J Dairy Sci. 2024 Feb 16:S0022-0302(24)00482-X. doi: 10.3168/jds.2023-23699. Online ahead of print.

ABSTRACT

Fertility in dairy cattle has declined as an unintended consequence of single trait selection for high milk yield. The unfavorable genetic correlation between milk yield and fertility is now well-documented, however, the underlying physiological mechanisms are still uncertain. To understand the relationship between these traits, we developed a method that clusters variants with similar patterns of effects and, after the integration of gene expression data, identifies the genes through which they are likely to act. Biological processes that are enriched in the genes of each cluster were then identified. We identified several clusters with unique patterns of effects. One of the clusters included variants associated with increased milk yield and decreased fertility, where the 'archetypal' variant (i.e., the one with the largest effect) was associated with the gene GC, while others were associated with TRIM32, LRRK2, and U6. These genes have been linked to transcription and alternative splicing, suggesting that these processes are likely contributors to the unfavorable relationship between the 2 traits. Another cluster, with archetypal variant near DGAT1 and including variants associated with CDH2, BTRC, SFRP2, ZFHX3, and SLITRK5, appeared to affect milk yield but have little effect on fertility. These genes have been linked to insulin, adipose tissue, and energy metabolism. A third cluster with archetypal variant near ZNF613 and including variants associated with ROBO1, EFNA5, PALLD, GPC6, and PTPRT were associated with fertility but not milk yield. These genes have been linked to GnRH neuronal migration, embryonic development, and/or ovarian function. The use of archetypal clustering to group variants with similar patterns of effects may assist in identifying the biological processes underlying correlated traits. The method is hypothesis-generating and requires experimental confirmation. However, we have uncovered several novel mechanisms potentially affecting milk production and fertility such as GnRH neuronal migration. We anticipate our method to be a starting point for experimental research into novel pathways which have been previously unexplored within the context of dairy production.

PMID:38369117 | DOI:10.3168/jds.2023-23699

Metab Eng. 2024 Feb 16:S1096-7176(24)00020-X. doi: 10.1016/j.ymben.2024.02.004. Online ahead of print.

ABSTRACT

Sustainable aviation fuel (SAF) will significantly impact global warming in the aviation sector, and important SAF targets are emerging. Isoprenol is a precursor for a promising SAF compound DMCO (1,4-dimethylcyclooctane) and has been produced in several engineered microorganisms. Recently, Pseudomonas putida has gained interest as a future host for isoprenol bioproduction as it can utilize carbon sources from inexpensive plant biomass. Here, we engineer metabolically versatile host P. putida for isoprenol production. We employ two computational modeling approaches (Bilevel optimization and Constrained Minimal Cut Sets) to predict gene knockout targets and optimize the "IPP-bypass" pathway in P. putida to maximize isoprenol production. Altogether, the highest isoprenol production titer from P. putida was achieved at 3.5 g/L under fed-batch conditions. This combination of computational modeling and strain engineering on P. putida for an advanced biofuels production has vital significance in enabling a bioproduction process that can use renewable carbon streams.

PMID:38369052 | DOI:10.1016/j.ymben.2024.02.004

Biochim Biophys Acta Mol Cell Res. 2024 Feb 16:119688. doi: 10.1016/j.bbamcr.2024.119688. Online ahead of print.

ABSTRACT

Programmed cell death, in particular apoptosis, is essential during development and tissue homeostasis, and also is the primary strategy to induce cancer cell death by cytotoxic therapies. Precision therapeutics targeting TRAIL death receptors are being evaluated as novel anti-cancer agents, while in parallel highly specific proteasome inhibitors have gained approval as drugs. TRAIL-dependent signalling and proteasomal control of cellular proteostasis are intricate processes, and their interplay can be exploited to enhance therapeutic killing of cancer cells in combination therapies. This review provides detailed insights into the complex signalling of TRAIL-induced pathways and the activities of the proteasome. It explores their core mechanisms of action, pharmaceutical druggability, and describes how their interplay can be strategically leveraged to enhance cell death responses in cancer cells. Offering this comprehensive and timely overview will allow to navigate the complexity of the processes governing cell death mechanisms in TRAIL- and proteasome inhibitor-based treatment conditions.

PMID:38368955 | DOI:10.1016/j.bbamcr.2024.119688

J Autoimmun. 2024 Feb 17;144:103177. doi: 10.1016/j.jaut.2024.103177. Online ahead of print.

ABSTRACT

Psoriasis (PS) and atopic dermatitis (AD) are common skin inflammatory diseases characterized by hyper-responsive keratinocytes. Although, some cytokines have been suggested to be specific for each disease, other cytokines might be central to both diseases. Here, we show that Tumor necrosis factor superfamily member 14 (TNFSF14), known as LIGHT, is required for experimental PS, similar to its requirement in experimental AD. Mice devoid of LIGHT, or deletion of either of its receptors, lymphotoxin β receptor (LTβR) and herpesvirus entry mediator (HVEM), in keratinocytes, were protected from developing imiquimod-induced psoriatic features, including epidermal thickening and hyperplasia, and expression of PS-related genes. Correspondingly, in single cell RNA-seq analysis of PS patient biopsies, LTβR transcripts were found strongly expressed with HVEM in keratinocytes, and LIGHT was upregulated in T cells. Similar transcript expression profiles were also seen in AD biopsies, and LTβR deletion in keratinocytes also protected mice from allergen-induced AD features. Moreover, in vitro, LIGHT upregulated a broad spectrum of genes in human keratinocytes that are clinical features of both PS and AD skin lesions. Our data suggest that agents blocking LIGHT activity might be useful for therapeutic intervention in PS as well as in AD.

PMID:38368767 | DOI:10.1016/j.jaut.2024.103177

Plant Mol Biol. 2024 Feb 18;114(2):21. doi: 10.1007/s11103-024-01422-3.

ABSTRACT

Arbuscular mycorrhizal symbiosis (AM) is a beneficial trait originating with the first land plants, which has subsequently been lost by species scattered throughout the radiation of plant diversity to the present day, including the model Arabidopsis thaliana. To explore if elements of this apparently beneficial trait are still present and could be reactivated we generated Arabidopsis plants expressing a constitutively active form of Interacting Protein of DMI3, a key transcription factor that enables AM within the Common Symbiosis Pathway, which was lost from Arabidopsis along with the AM host trait. We characterize the transcriptomic effect of expressing IPD3 in Arabidopsis with and without exposure to the AM fungus (AMF) Rhizophagus irregularis, and compare these results to the AM model Lotus japonicus and its ipd3 knockout mutant cyclops-4. Despite its long history as a non-AM species, restoring IPD3 in the form of its constitutively active DNA-binding domain to Arabidopsis altered expression of specific gene networks. Surprisingly, the effect of expressing IPD3 in Arabidopsis and knocking it out in Lotus was strongest in plants not exposed to AMF, which is revealed to be due to changes in IPD3 genotype causing a transcriptional state, which partially mimics AMF exposure in non-inoculated plants. Our results indicate that molecular connections to symbiosis machinery remain in place in this nonAM species, with implications for both basic science and the prospect of engineering this trait for agriculture.

PMID:38368585 | DOI:10.1007/s11103-024-01422-3

J Struct Biol. 2024 Feb 15:108067. doi: 10.1016/j.jsb.2024.108067. Online ahead of print.

ABSTRACT

Cellular cryo-electron tomography (cryo-ET) has emerged as a key method to unravel the spatial and structural complexity of cells in their near-native state at unprecedented molecular resolution. To enable quantitative analysis of the complex shapes and morphologies of lipid membranes, the noisy three-dimensional (3D) volumes must be segmented. Despite recent advances, this task often requires considerable user intervention to curate the resulting segmentations. Here, we present ColabSeg, a Python-based tool for processing, visualizing, cleaning, and fitting membrane segmentations from cryo-ET data for downstream analysis. ColabSeg makes many well-established algorithms for point-cloud processing easily available to the broad community of structural biologists for applications in cryo-ET through its graphical user interface (GUI). We demonstrate the usefulness of the tool with a range of use cases and biological examples. Finally, for a large Mycoplasma pneumoniae dataset of 50 tomograms, we show how ColabSeg enables high-throughput membrane segmentation, which can be used as valuable training data for fully automated convolutional neural network (CNN)-based segmentation.

PMID:38367824 | DOI:10.1016/j.jsb.2024.108067

Metab Eng. 2024 Feb 15:S1096-7176(24)00024-7. doi: 10.1016/j.ymben.2024.02.008. Online ahead of print.

ABSTRACT

Metabolites, as small molecules, can act not only as substrates to enzymes, but also as effectors of activity of proteins with different functions, thereby affecting various cellular processes. While several experimental techniques have started to catalogue the metabolite-protein interactions (MPIs) present in different cellular contexts, characterizing the functional relevance of MPIs remains a challenging problem. Computational approaches from the constrained-based modeling framework allow for predicting MPIs and integrating their effects in the in silico analysis of metabolic and physiological phenotypes, like cell growth. Here, we provide a classification of all existing constraint-based approaches that predict and integrate MPIs using genome-scale metabolic networks as input. In addition, we benchmark the performance of the approaches to predict MPIs in a comparative study using different features extracted from the model structure and predicted metabolic phenotypes with the state-of-the-art metabolic networks of Escherichia coli and Saccharomyces cerevisiae. Lastly, we provide an outlook for future, feasible directions to expand the consideration of MPIs in constraint-based modeling approaches with wide biotechnological applications.

PMID:38367764 | DOI:10.1016/j.ymben.2024.02.008

Biosystems. 2024 Feb 15:105157. doi: 10.1016/j.biosystems.2024.105157. Online ahead of print.

ABSTRACT

Evolution, self-replication and ontogenesis are highly dynamic, irreversible and self-organizing processes dissipating energy. While progress has been made to decipher the role of thermodynamics in cellular fission, it is not yet clear how entropic balances shape organism growth and aging. This paper derives a general dissipation theory for the life-history of organisms. It implies a self-regulated entropy production facilitating exponential growth within a hierarchical and entropy lowering self-organization. The theory predicts ceilings in energy expenditures imposed by geometric constrains, which promote thermal optimality during development, and a dissipative scaling across organisms consistent with ecological scaling laws combining isometric and allometric terms. The theory also illustrates how growing organisms can tolerate damage through continuous extension and production of new dissipative structures low in entropy. However, when organisms reduce their rate of cell division and reach a steady adult state, they become thermodynamically unstable, increase internal entropy by accumulating damage, and age.

PMID:38367762 | DOI:10.1016/j.biosystems.2024.105157

Biochem Biophys Res Commun. 2024 Feb 8;703:149597. doi: 10.1016/j.bbrc.2024.149597. Online ahead of print.

ABSTRACT

Myosin family proteins are ATP-driven, actin filament-based motor proteins that generate force along actin filaments. In in vitro actin filament gliding assays, certain myosins generate rotation of gliding actin filaments around their long axes. In this study, we assessed the effects of temperature on the corkscrewing motion of actin filaments, including factors like gliding and rotational velocities and corkscrewing pitch. The corkscrewing motion was driven by a nonprocessive, full-length single-headed Drosophila myosin IC attached to an antibody adsorbed onto a cover glass. We performed an in vitro actin filament corkscrewing assay at temperatures ranging from 25 °C to 35 °C. We found that the gliding and rotational velocities and the pitch of corkscrewing actin filaments generated by myosin IC molecules increased with increasing temperature. Since the pitch is determined by dividing the gliding velocity by the rotational velocity, an increase in the pitch indicates that the gliding velocity increased faster than the rotational velocity with increasing temperature. These results suggest that temperature has distinct effects on the gliding and rotational forces produced by myosin IC, with implications for interpreting the temperature effect on torque-generation mechanisms driven by myosins on actin filaments at physiological temperatures.

PMID:38367512 | DOI:10.1016/j.bbrc.2024.149597

STAR Protoc. 2024 Feb 15;5(1):102887. doi: 10.1016/j.xpro.2024.102887. Online ahead of print.

ABSTRACT

Functional precision oncology-a strategy based on perturbing primary tumor cells from cancer patients-could provide a road forward for personalized treatment. Here, we present a comprehensive protocol covering generation and culture of patient-derived colorectal organoids, isolation and expansion of tumor-infiltrating lymphocytes (TILs), and isolation and culture of peripheral blood mononuclear cells (PBMCs). With this protocol, samples fulfilling the demands for performing multi-omics analysis, e.g., RNA sequencing (RNA-seq), whole-exome sequencing (WES), single-cell RNA sequencing (scRNA-seq), and (phospho-)proteomics, can be generated. For complete details on the use and execution of this protocol, please refer to Plattner et al. (2023).1.

PMID:38367233 | DOI:10.1016/j.xpro.2024.102887

Tissue Eng Regen Med. 2024 Feb 17. doi: 10.1007/s13770-023-00621-1. Online ahead of print.

ABSTRACT

BACKGROUND: Dysregulation of skin metabolism is associated with a plethora of diseases such as psoriasis and dermatitis. Until now, reconstructed human skin (RhS) models lack the metabolic potential of native human skin, thereby limiting their relevance to study human healthy and diseased skin. We aimed to determine whether incorporation of an adipocyte-containing hypodermis into RhS improves its metabolic potential and to identify major metabolic pathways up-regulated in adipose-RhS.

METHODS: Primary human keratinocytes, fibroblasts and differentiated adipose-derived stromal cells were co-cultured in a collagen/fibrin scaffold to create an adipose-RhS. The model was extensively characterized structurally in two- and three-dimensions, by cytokine secretion and RNA-sequencing for metabolic enzyme expression.

RESULTS: Adipose-RhS showed increased secretion of adipokines. Both RhS and adipose-RhS expressed 29 of 35 metabolic genes expressed in ex vivo native human skin. Addition of the adipose layer resulted in up-regulation of 286 genes in the dermal-adipose fraction of which 7 were involved in phase I (CYP19A1, CYP4F22, CYP3A5, ALDH3B2, EPHX3) and phase II (SULT2B1, GPX3) metabolism. Vitamin A, D and carotenoid metabolic pathways were enriched. Additionally, pro-inflammatory (IL-1β, IL-18, IL-23, IL-33, IFN-α2, TNF-α) and anti-inflammatory cytokine (IL-10, IL-12p70) secretion was reduced in adipose-RhS.

CONCLUSIONS: Adipose-RhS mimics healthy native human skin more closely than traditional RhS since it has a less inflamed phenotype and a higher metabolic activity, indicating the contribution of adipocytes to tissue homeostasis. Therefore it is better suited to study onset of skin diseases and the effect of xenobiotics.

PMID:38367122 | DOI:10.1007/s13770-023-00621-1

Cell. 2024 Feb 9:S0092-8674(24)00066-7. doi: 10.1016/j.cell.2024.01.029. Online ahead of print.

ABSTRACT

Carbohydrate intolerance, commonly linked to the consumption of lactose, fructose, or sorbitol, affects up to 30% of the population in high-income countries. Although sorbitol intolerance is attributed to malabsorption, the underlying mechanism remains unresolved. Here, we show that a history of antibiotic exposure combined with high fat intake triggered long-lasting sorbitol intolerance in mice by reducing Clostridia abundance, which impaired microbial sorbitol catabolism. The restoration of sorbitol catabolism by inoculation with probiotic Escherichia coli protected mice against sorbitol intolerance but did not restore Clostridia abundance. Inoculation with the butyrate producer Anaerostipes caccae restored a normal Clostridia abundance, which protected mice against sorbitol-induced diarrhea even when the probiotic was cleared. Butyrate restored Clostridia abundance by stimulating epithelial peroxisome proliferator-activated receptor-gamma (PPAR-γ) signaling to restore epithelial hypoxia in the colon. Collectively, these mechanistic insights identify microbial sorbitol catabolism as a potential target for approaches for the diagnosis, treatment, and prevention of sorbitol intolerance.

PMID:38366592 | DOI:10.1016/j.cell.2024.01.029

Cancer Cell. 2024 Feb 9:S1535-6108(24)00015-1. doi: 10.1016/j.ccell.2024.01.010. Online ahead of print.

ABSTRACT

Atezolizumab (anti-PD-L1), combined with carboplatin and etoposide (CE), is now a standard of care for extensive-stage small-cell lung cancer (ES-SCLC). A clearer understanding of therapeutically relevant SCLC subsets could identify rational combination strategies and improve outcomes. We conduct transcriptomic analyses and non-negative matrix factorization on 271 pre-treatment patient tumor samples from IMpower133 and identify four subsets with general concordance to previously reported SCLC subtypes (SCLC-A, -N, -P, and -I). Deeper investigation into the immune heterogeneity uncovers two subsets with differing neuroendocrine (NE) versus non-neuroendocrine (non-NE) phenotypes, demonstrating immune cell infiltration hallmarks. The NE tumors with low tumor-associated macrophage (TAM) but high T-effector signals demonstrate longer overall survival with PD-L1 blockade and CE versus CE alone than non-NE tumors with high TAM and high T-effector signal. Our study offers a clinically relevant approach to discriminate SCLC patients likely benefitting most from immunotherapies and highlights the complex mechanisms underlying immunotherapy responses.

PMID:38366589 | DOI:10.1016/j.ccell.2024.01.010

Phys Rev E. 2024 Jan;109(1-1):014403. doi: 10.1103/PhysRevE.109.014403.

ABSTRACT

Collective motion of locally interacting agents is found ubiquitously throughout nature. The inability to probe individuals has driven longstanding interest in the development of methods for inferring the underlying interactions. In the context of heterogeneous collectives, where the population consists of individuals driven by different interactions, existing approaches require some knowledge about the heterogeneities or underlying interactions. Here, we investigate the feasibility of identifying the identities in a heterogeneous collective without such prior knowledge. We numerically explore the behavior of a heterogeneous Vicsek model and find sufficiently long trajectories intrinsically cluster in a principal component analysis-based dimensionally reduced model-agnostic description of the data. We identify how heterogeneities in each parameter in the model (interaction radius, noise, population proportions) dictate this clustering. Finally, we show the generality of this phenomenon by finding similar behavior in a heterogeneous D'Orsogna model. Altogether, our results establish and quantify the intrinsic model-agnostic statistical disentanglement of identities in heterogeneous collectives.

PMID:38366514 | DOI:10.1103/PhysRevE.109.014403

Phys Rev E. 2024 Jan;109(1-1):014612. doi: 10.1103/PhysRevE.109.014612.

ABSTRACT

We introduce a numerical method to extract the parameters of run-and-tumble dynamics from experimental measurements of the intermediate scattering function. We show that proceeding in Laplace space is unpractical and employ instead renewal processes to work directly in real time. We first validate our approach against data produced using agent-based simulations. This allows us to identify the length and time scales required for an accurate measurement of the motility parameters, including tumbling frequency and swim speed. We compare different models for the run-and-tumble dynamics by accounting for speed variability at the single-cell and population level, respectively. Finally, we apply our approach to experimental data on wild-type Escherichia coli obtained using differential dynamic microscopy.

PMID:38366485 | DOI:10.1103/PhysRevE.109.014612

Nat Methods. 2024 Feb 16. doi: 10.1038/s41592-024-02197-7. Online ahead of print.

NO ABSTRACT

PMID:38366242 | DOI:10.1038/s41592-024-02197-7

Pharm Res. 2024 Feb 16. doi: 10.1007/s11095-024-03656-8. Online ahead of print.

ABSTRACT

Drugs with multiple targets, often annotated as 'unselective', 'promiscuous', 'multitarget', or 'polypharmacological', are widely considered in both academic and industrial research as a high risk due to the likelihood of adverse effects. However, retrospective analyses have shown that particularly approved drugs bear rich polypharmacological profiles. This raises the question whether our perception of the specificity paradigm ('one drug-one target concept') is correct - and if specifically multitarget drugs should be developed instead of being rejected. These questions provoke a paradigm shift - regarding the development of polypharmacological drugs not as a 'waste of investment', but acknowledging the existence of a 'lack of investment'. This perspective provides an insight into modern drug development highlighting latest drug candidates that have not been assessed in a broader polypharmacology-based context elsewhere embedded in a historic framework of classical and modern approved multitarget drugs. The article shall be an inspiration to the scientific community to re-consider current standards, and more, to evolve to a better understanding of polypharmacology from a challenge to an opportunity.

PMID:38366233 | DOI:10.1007/s11095-024-03656-8