The global burden of respiratory diseases is very high and still on the rise, prompting the need for accurate models for basic and translational research. Several model systems are currently available ranging from simple airway cell cultures to complex tissue-engineered lungs. In recent years, human lung organoids have been established as highly transferrable three-dimensional in vitro model systems for lung research. For acute infectious and chronic inflammatory diseases as well as lung cancer, human lung organoids have opened possibilities for precise in vitro research and a deeper understanding of mechanisms underlying lung injury and regeneration. Human lung organoids from induced pluripotent stem cells or from adult stem cells of patients’ samples introduce tools for understanding developmental processes and personalized medicine approaches. When further state-of-the-art technologies and protocols come into use, the full potential of human lung organoids can be harnessed. High-throughput assays in drug development, gene therapy, and organoid transplantation are current applications of organoids in translational research. In this review, we emphasize novel approaches in translational and personalized medicine in lung research focusing on the use of human lung organoids. The global incidence of respiratory diseases is high and still rising, even without the recent coronavirus disease 2019 (COVID-19) pandemic and its associated morbidity and mortality . Lung caTo fully comprehend the underlying mechanisms of health and disease in the respiratory system, research models need to become more accurate with regard to the representation of physiological and pathophysiological processes. Models should mirror specific aspects of the in vivo situation as precisely as possible to grant transferability for clinical studies, which often require higher model complexity. Current models such as in vitro generated human lung organoids, which represent three-dimensional (3D), multi-cell types-containing, and self-assembling structures, offer new insights into tissue-specific intercellular communication processes mimicking parenchymal interactions. A better understanding of lung physiology, injury, and repair is necessary to develop suitable therapeutic approaches for various lung diseases. Therefore, 3D organoid cultures may be used to study underlying epithelial mechanisms. Further, the development of expandable organoids grown from stem cells or patient tissue samples provides a method for high-throughput screening of drugs . This reThe lower respiratory tract consists of the trachea, bronchi, and bronchioli, representing the lower conducting airways and the alveoli. The conducting airways are responsible for mucociliary clearance and consist mainly of basal, ciliated, club, and goblet cells . Gas excThe epithelial composition changes from proximal to distal airways. Cell populations in the tracheal and intermediate bronchi are quite similar, as they contain mainly basal cells and fewer differentiated cell types. Distal airways have a higher percentage of secretory and multiciliated cells . Basal cThe high complexity of the lung anatomy and physiology results in the exceptional need for well-developed model systems and, therefore, it is important to carefully choose which model system best meets the needs of a given research question. In Simple immortalized cell line cultures are the easiest and fastest model systems, making their application common in lung research. These are typically used to answer basic research questions related to airway cell pathophysiology . CommonlAir–liquid interface (ALI) cultures have been developed to increase the complexity of cell culture model systems as they better represent physiological conditions and involve cellular differentiation processes. These culture systems can be established with primary airway epithelial cells or cell lines such as BEAS2B or A549, which grow as pseudostratified epithelium with a mucociliary phenotype ,33. To aOverall, compared to simple 2D cell culture models, ALI cultures are far more analogous to the in vivo situation and may be used to analyze drug delivery mechanisms, differentiation processes, and mechanisms of development of and interference with epithelial barrier integrity.Precision cut lung slices (PCLS) are thin slices of tissue taken from freshly obtained human or animal lung samples, which can be collected from surgical sections ,39. The Concluding, PCLS represents a highly complex ex vivo model system for a variety of scientific questions; nevertheless, limiting factors such as tissue availability and maintenance need to be considered.Organoids are 3D cell culture systems derived from adult stem cells or pluripotent stem cells. Under well-defined culture conditions, these cells have the ability to proliferate and differentiate into various epithelial cell types quite similar to in vivo. During this process, the cells self-assemble into spherical structures ,47. LungAnother new approach to highly complex lung model systems is decellularized lung scaffolds. To obtain these scaffolds, lung tissue is decellularized using physical, chemical, and/or enzymatic treatments. The remaining extracellular matrix is reseeded with induced pluripotent stem cells (iPSC). The matrix scaffold provides both structural and biochemical support . VariousDecellularized lung scaffolds may be used in the future to bioengineer new lungs, potentially replacing lacking donor lungs or being used as a highly complex model system in research. However, several challenges still remain to be solved as outlined above.While searching for new and suitable model systems with a high complexity and high potential to reflect the in vivo situation, one reads often about microphysiological systems. The definition of such systems differs depending on the source. Some authors even include organoids in this definition, whilst others use microphysiological systems as a synonym for organs-on-a-chip. Microphysiological systems should feature the main anatomical and physiological, hence structural and functional, characteristics of the human organ . In orgaIn vivo experiments are highly suited to investigate questions related to the whole organism or affecting several different aspects of it . HoweverOrganoids, despite not being the most complex in vitro model system, are one of the most developed complex systems as they represent a reasonable compromise between the level of complexity and necessary efforts and thus are a crucial tool for basic and translational research. They ideally close the gap between simple in vitro models and the in vivo situation. Therefore, the following chapters will focus on organoids as novel tools in lung research with high potential in translational and personalized medicine.As shortly introduced above, organoids are 3D, self-assembling cellular structures, composed of several different organ-specific cell types that execute their organ-specific cell function . OrganoiDifferent kinds of lung organoids can be grown from a variety of primary cells, including embryonic stem cells, induced pluripotent stem cells or adult stem cells . Each tyIn conclusion, for a great variety of scientific questions regarding lung diseases and (patho-)physiological processes in the lung, alveolar, or bronchial organoids can be applied. There are many protocols yet available to handle them in an easy way and to grow a long-term, nearly endless source of organoid culture ,82,86,91Nowadays, due to emerging new technologies such as high-throughput assays, single-cell analysis, and bioinformatic tools, research has a greater potential to develop novel diagnostics and therapies for a wide range of diseases. However, finding suitable models for specific research questions remains often challenging. Model systems with a high transferability to the human in vivo situation is required for translational medicine in order to close the gap between fundamental research and clinical applications. A suitable solution is represented by the aforementioned complex 3D organoid model systems, as they consist of different functional organ-specific cell types with the ability to proliferate, differentiate and organize in a way very similar to in vivo processes. Miller et al.  depictedSzabo et al.  suggeste+Foxi1 pulmonary ionocytes specifically expressing CFTR, which might be involved in the pathomechanisms of CF [CF is an autosomal recessive disorder caused by mutations in the gene encoding for the CFTR channel resulting in its dysfunction. CFTR is essential for the physiological mucociliary clearance, hence its dysfunction results in mucus retention followed by airway inflammation and increased risk of airway infections . Using sms of CF . Furtherms of CF  used humms of CF . To evalms of CF  establisms of CF . Forskolms of CF . McCaulems of CF  were ablms of CF  showed tThus, organoids add from our point of view several great advantages to this research area, especially since CF is still not curable.+ basal cells under the influence of for instance TGF-β signaling or hiCTHRCI pro-fibrotic mesenchyme. As hAEC2 with basal cell characteristics are found in IPF lungs, driving this research on organoids forward could further advance insights into IPF pathogenesis. In our assessment, organoids as complex in vitro model systems have a high potential to generate new insights in IPF pathogeneses and hence the development of therapeutic strategies, as cell–cell interactions and co-culturing with mesenchymal cells is suitable to mirror the in vivo situation of fibrotic lungs.Another common lung disease is IPF, a severe chronic disorder associated with several risk factors leading to the remodeling processes of the lung epithelium with increased production of extracellular matrix ,103. Jae+ and SCGB3A2+ cell population shows a modified transcriptome profile in patients with COPD leading to altered AT2 cell conditions. Further, transitioning of RAS into AT2 cells seems to be affected by smoke injury as a pack-year dependent increase in SCGB3A2+ and LAMP3+ cell populations was shown. Song et al. [COPD is a common disease worldwide, affecting primarily older patients with multimorbidity after being exposed to several risk factors such as cigarette smoke. COPD is an inflammatory airway disease, manifested by chronic bronchitis and emphysema based on various underlying pathomechanisms . This etg et al.  tested ag et al. . Despiteg et al. ,112. Dang et al.  were ablg et al. ,113. COPg et al.  used theThe COVID-19 pandemic pointed again to the persistent importance of research in infectious airway diseases. It has been demonstrated that lung organoids have considerable potential for application in translational research to study infectious diseases. Chen et al.  and PoroAnother possibility to use organoids in personalized medicine is the generation of tumor organoids from non-small cell lung carcinoma (NSCLC) patients ,121. NSCTo further expand the potential of personalized medicine, molecular methods can not only be used to induce mutations in organoids for specific drug screenings or fundamental research but can also be applied to correct altered genes as a methodological contribution to the rapidly developing field of gene therapy. Leibel et al.  demonstrDifferent approaches have been performed for reseeding decellularized lung scaffolds populated with autologous cells followed by the transplantation of the resulting organoid structures. Hayes et al.  suggesteIn the future, due to the development of patient-based model systems that mimic in vivo conditions up to a high level, patients will receive individual therapies that are best suited to their specific needs and conditions .As this review demonstrates, human lung organoids present a ground-breaking method for research on lung physiology and pathology, even though the method is still in its infancy. There is a number of established protocols for the expansion and culture of human lung organoids available. Whereas current protocols focus on modelling compartments of the respiratory system and co-culture of different lung cell types as functional organoids, the next step will be the further development of advanced organoids additionally combining immunological settings with perfusable vasculature for an even more accurate representation of the branching architecture of the respiratory system ,135. In


The rising global prevalence of myopia is a growing concern for clinicians, as it predisposes patients to severe ocular pathologies including glaucoma. High myopia can be associated with clinical features that resemble glaucomatous damage, which make an accurate glaucoma diagnosis challenging, particularly among patients with normal intraocular pressures. These patients may also present with established visual field defects which can mimic glaucoma, and standard imaging technology is less useful in disease detection and monitoring due to the lack of normative data for these anatomically unique eyes. Progression over time remains the most critical factor in facilitating the detection of early glaucomatous changes, and thus careful longitudinal follow-up of high-risk myopic patients is the most important aspect of management. Here, we review our current understanding of the complex relationship between myopia and glaucoma, and the diagnostic challenges and limitations of current testing protocols including visual field, intraocular pressure, and imaging. Furthermore, we discuss the clinical findings of two highly myopic patients with suspected glaucoma. Myopia has become increasingly prevalent worldwide, reflecting the significant changes in lifestyle behaviors and predominant indoor near work among the younger population, particularly East Asians ,2. DurinThe association between myopia and primary open angle glaucoma (POAG) is well established ,10,11,12The mechanisms for the relationship between myopia and glaucoma are incompletely understood. The mechanical hypothesis relates to the differing anatomy of myopic eyes, which have longer axial lengths and thinner sclera . These cPeripapillary anatomical changes are also likely to play a role in the increased susceptibility for glaucomatous optic neuropathy in high myopia ,29. BetaThe axial elongation-induced optic disc tilt and subsequent stretching of the temporal peripapillary scleral flange results in characteristic changes to the optic nerve head, which, when affected by glaucoma, have important differences to non-myopic glaucomatous optic nerves. Myopic discs are larger and can have a greater disc area . In addiDifferentiating myopia-related optic neuropathy and normal tension glaucoma (NTG) can be very challenging due to the constellation of clinical findings particularly associated with high myopia. It has been well recognized that myopic patients with normal intraocular pressures (IOPs) can present with glaucomatous visual field defects, which can be attributed to myopia rather than to glaucoma ,41,42,43Given the many different types of visual field defects associated with the myopia described, most recently, a proposed classification system for highly myopic eyes without glaucoma or pathological changes was suggested as a way to standardize reporting . DefectsThe role of IOP in myopic glaucoma patients can present both diagnostic and management challenges. In numerous previous population-based studies, NTG has been found to comprise the majority of open-angle glaucoma (OAG) in Asians, with rates ranging from 52–92% ,50,51,52Recent genetic research has also implicated IOP as a key mediator in the causal pathway between myopia and POAG . MendeliThere is evidence to suggest that baseline IOP, and IOP diurnal patterns may differ between myopes and non-myopes. Young myopic adults without glaucoma have been found to have higher daytime IOPs compared to those without myopia, as well as higher nocturnal supine IOP elevation ,57,58,59In addition to glaucomatous-like visual field defects, optic nerve morphology of myopes and particularly of high myopes, is often abnormal and thus difficult to assess objectively using currently available imaging technology. Myopes are known to have a decreased retinal nerve fiber layer (RNFL) at baseline and RNFL bundles can be shifted temporally, resulting in thicker temporal quadrants and nasal thinning, which can be misleading if compared to the inbuilt normative database within which moderate–high myopic patients are not well represented ,66,67. FThe ability to detect myopia-associated glaucoma-like optic neuropathy has also been improved by advances in swept-source OCT (SS-OCT) and OCT angiography (OCTA) ,72,73. ISeveral previous studies have demonstrated that the ganglion cell complex (GCC) parameters are superior to RNFL at detecting glaucoma in the context of high myopia ,79,80,81The two cases below demonstrate the spectrum of disease seen in myopic patients also suspected to have glaucoma. In addition to history, examination and investigations, adequate follow-up over time is the most critical factor in ensuring the correct diagnosis and management.A 59-year-old Asian male with a myopic prescription of −8.0 D OD and −7.0 D OS presented with evidence of progression in his visual field defects over five years of follow-up. He had a diagnosis of NTG, and his IOPs had been stable in the mid-teens for several years on topical medications. Optic disc examination revealed slightly tilted, cupped discs with mild peripapillary atrophy. OCT RNFL demonstrated stable mild right inferior thinning, and more pronounced left superior thinning, with bilateral superior–temporal ganglion–cell complex defects A. The viA 50-year-old female Asian with a myopic prescription of −15.75 D OD and −15.0 D OS presented for a review of visual field defects noted at the baseline examination five years prior. She had been followed as a glaucoma suspect/ocular hypertensive, with IOP at 20 OU on latanoprost in both eyes. Her optic nerves were tilted and ovoid in shape, with pronounced peripapillary atrophy, worse in the left eye A. OCT deOur understanding of the complex relationship between myopia and glaucoma continues to develop, particularly with the increasing prevalence of myopia worldwide. Myopia is an established risk factor for OAG, but often can present with normal IOP which complicates the diagnosis and management. Myopia, in particular axial high myopia, is associated with anatomical changes with resultant characteristic differences in the clinical appearance of the optic nerve head and peripapillary region, making the assessment of optic nerve cupping especially challenging. These patients often present with established visual field defects which can mimic glaucoma, and standard imaging technology is less useful in disease detection and monitoring due to the lack of normative data for these anatomically unique eyes. Progression over time remains the most critical factor, and thus careful longitudinal follow-up of these patients is the most important aspect of management. As our technology continues to improve, there will no doubt be further advances to aid the detection and management of patients with myopia and glaucoma.


The widespread push to invest in local cancer therapies comes from the need to overcome the limitations of systemic treatment options. In contrast to intravenous administration, local treatments using intratumoral or peritumoral injections are independent of tumor vasculature and allow high concentrations of therapeutic agents to reach the tumor site with minimal systemic toxicity. Injectable biodegradable hydrogels offer a clear advantage over other delivery systems because the former requires no surgical procedures and promotes drug retention at the tumor site. More precisely, in situ gelling systems based on poloxamers have garnered considerable attention due to their thermoresponsive behavior, biocompatibility, ease of preparation, and possible incorporation of different anticancer agents. Therefore, this review focuses on the use of injectable thermoresponsive hydrogels based on poloxamers and their physicochemical and biological characterization. It also includes a summary of these hydrogel applications in local cancer therapies using chemotherapy, phototherapy, immunotherapy, and gene therapy. Local cancer therapy holds great potential to address the shortcomings of systemic treatment options, namely the lack of specificity for the target, low therapeutic efficiency, and drug resistance.Different from intravenous (IV) administration, local treatments using intratumoral (IT) or peritumoral (PT) injections allow high concentrations of therapeutic agents to reach the tumor site, bypassing the bloodstream and non-specific interactions with healthy tissues . MoreoveIn contrast to delivery systems based on implants  and particles, injectable biodegradable hydrogels require non-surgical procedures and promote retention of free or encapsulated drugs at the tumor site . Indeed,Injectable gels include pre-formed gels with shear-thinning and self-healing properties  and in sIn this review, we emphasize the use of poloxamers in the development of injectable thermoresponsive hydrogels and their characterization. The extensive application of injectable poloxamer hydrogels in local cancer therapy, including chemotherapy, phototherapy, immunotherapy, and gene therapy, is also summarized.Hydrogels are thermoresponsive if they respond to changes in temperature. A case in point is thermoresponsive polymer solutions exhibiting a sol–gel phase transition upon the shift from room to body temperature 37 °C). The temperature at which the transition from one phase to two phases (polymer-enriched and aqueous phases) takes place is termed the “critical solution temperature” of the polymer -b-poly(2-dimethylamino) ethyl methacrylate) and negatively charged survivin antisense oligonucleotide, Zhao et al.  developeAt the end of this subsection, A myriad of in situ gelling systems triggered by temperature changes has been developed for the IT or PT administration of different therapeutic agents. Among thermoresponsive polymers, poloxamer-based hydrogels are in the spotlight due to their low cost, simplicity of preparation, and compatibility with biological systems ,98.Over the past two decades, poloxamer dispersions have been proposed as injectable formulations to assist local cancer treatment using chemotherapy, phototherapy, immunotherapy, and gene therapy. However, the application of injectable poloxamer hydrogels for local tumor administration remains in the proof-of-concept stage, despite promising preclinical (in vitro and in vivo) outcomes. First, it is highly recommended that poloxamers are modified or used in novel combinations of polymers to reduce the erosion rate of conventional poloxamer hydrogels and ensure precise delivery. Moreover, the developed hydrogels are more likely to reach the clinical testing phase if researchers evaluate therapeutic efficacy in larger animals  instead of using rodent models . In addiIn the future, injectable poloxamer hydrogels are expected to remain an exciting research topic not only for drug delivery but also for tissue engineering  and cart


As microbiome research has progressed, it has become clear that most, if not all, eukaryotic organisms are hosts to microbiomes composed of prokaryotes, other eukaryotes, and viruses. Fungi have only recently been considered holobionts with their own microbiomes, as filamentous fungi have been found to harbor bacteria (including cyanobacteria), mycoviruses, other fungi, and whole algal cells within their hyphae. Constituents of this complex endohyphal microbiome have been interrogated using multi-omic approaches. However, a lack of tools, techniques, and standardization for integrative multi-omics for small-scale microbiomes  has limited progress towards investigating and understanding the total diversity of the endohyphal microbiome and its functional impacts on fungal hosts. Understanding microbiome impacts on fungal hosts will advance explorations of how “microbiomes within microbiomes” affect broader microbial community dynamics and ecological functions. Progress to date as well as ongoing challenges of performing integrative multi-omics on the endohyphal microbiome is discussed herein. Addressing the challenges associated with the sample extraction, sample preparation, multi-omic data generation, and multi-omic data analysis and integration will help advance current knowledge of the endohyphal microbiome and provide a road map for shrinking microbiome investigations to smaller scales.Video AbstractThe online version contains supplementary material available at 10.1186/s40168-023-01634-7. Communities of microbes that exist in a particular environment, often referred to as microbiomes, have been universally observed across diverse ecosystems and biological niches including food products, soils, humans, and animals –3. ReseaFungi are both common and integral members of environmental and host-associated microbiomes, and their presence and functional contributions are known to significantly affect microbiome dynamics and larger ecological processes , 9. The Multi-omics techniques have rapidly gained popularity for investigating individual constituents and smaller subsets of fungal-associating communities but have yet to be used to interrogate entire endohyphal microbiomes. Due to their early discovery relative to other members of the endohyphal microbiome, bacterial endosymbionts represent the most frequently studied group of fungal associates. In line with canonical microbiome function, endohyphal bacterial associates have been shown to significantly alter fungal host function, development, and interactions with other organisms –21. CertMulti-omics approaches  have been foundational in elucidating the diversity and functional roles of the endohyphal microbiome. However, these investigations have also highlighted several challenges associated with performing integrative multi-omics studies on small-scale microbiomes. The development of methods and standards relating to sample preparation, data generation, data analysis, and data integration at these small physical (micro to nano) scales will be critical towards enabling holistic investigations of the endohyphal and other small-scale microbiomes.Many recent microbiome studies using multi-omics methods have centered around scaling up and capturing snapshots of entire environments or ecosystems. Interrogating large-scale microbiomes using multi-omics is informative for analyzing high-abundance sequences and biomolecules but can lack the resolution required for capturing contributions of potential underlying microbiomes of the constituents. In order to interrogate smaller, but potentially equally biologically relevant microbiomes, current techniques and tools for larger-scale investigations must be adjusted, and the development of novel protocols and methods is also warranted. Herein, progress on the utilization of integrative multi-omics for endohyphal microbiome investigations will be discussed along with current and future challenges relating to the application of these techniques to holistic studies of small-scale microbiomes.Multi-omics investigations have provided key insights regarding the presence, taxonomic composition, and functional implications of members of the endohyphal microbiome on fungal hosts including impacts on host reproduction and pathogenesis , 23, 24 Burkholderia-related endobacteria (BRE). Other fungal lineages, including Ascomycota and Basidiomycota, have been found to host endohyphal bacteria, but the distribution of these bacteria within fungal mycelial networks and their impacts on host physiology and functioning have been comparatively understudied [Multi-omics investigations on endohyphal microbiomes have been most widely conducted on members of the Mucoromycota, which frequently harbor members from either one or both of two groups of highly studied bacterial endosymbionts: Mollicutes-related endobacteria (MRE) and rstudied –27.Genomics- and metagenomics-based studies determined that MRE and BRE both have significantly reduced genome sizes and protein-coding content compared to closely related free-living bacteria, as well as reduced metabolic capacities –31. ThesRhizopus microsporus (Mucoromycota) isolates harboring BRE and those cured of their BRE partner revealed that the bacterial endosymbiont alters host gene expression, allowing it to control aspects of both asexual and sexual reproduction [Luteibacter, Gammaproteobacteria) interacts with its fungal host  prior to endohyphal establishment [Gigaspora margarita (Mucoromycota) cause a shift in primary metabolism of the fungal host and an increase in fungal antioxidant production, which in turn alters interaction dynamics between plants and the fungal host [R. microsporus transcriptome and metabolome indicated differences in lipid metabolism and composition during interactions with its BRE partner [Mycetohabitans rhizoxinica (Betaproteobacteria) in R. microsporus [Transcriptomics has been used to uncover the genes and putative functions involved in interactions between endohyphal bacteria and their hosts. For example, comparative transcriptomic experiments between oduction . Comparalishment . Additiogal host . Examina partner . To inverosporus .G. margarita [Paenibacillus (Bacilli) alters the lipid profiles of Thamnidium elegans (Mucoromycota) compared to other Mucoromycota fungi which do not host the bacterium [Mycoavidus cysteinexigens) substantially alters the Linnemannia elongata (Mucoromycota) transcriptome and metabolome, particularly with respect to fatty acid biosynthesis [Rhizopus-associated BRE, not the fungus itself [G. margarita with and without bacterial endosymbionts have shown that the endobacteria can significantly alter host protein expression and lipid profiles under several conditions and growth stages [Linnemannia elongata (Mucoromycota) and its bacterial endosymbiont Mycoavidus sp. (Betaproteobacteria) [L. elongata with and without Mycoavidus sp. showed that when the endobacterium is present, the production of fatty acids from the pyruvate pathway leads to high butyric acid and butyrate levels [Metabolomics studies have identified broad shifts in the fungal metabolome related to harboring endobacteria. For example, the presence of BRE was found to induce substantial shifts in the metabolome of argarita . Metabolacterium . Similarynthesis . In addis itself . Proteomh stages . Investiacteria) . Volatile levels .Geosiphon pyriformis (Mucoromycota), the first fungus found to internalize Nostoc, a nitrogen-fixing cyanobacterium [Exploratory studies involving other members of the endohyphal microbiome have lagged behind in numbers, but these studies have led to key findings. Multi-omic studies have facilitated the identification and corroboration of novel members of the endohyphal microbiome and have started to provide insights into how members within the microbiome interact with one another in addition to their interactions with the fungal host. Genomics and transcriptomics were used to explore genes of interest, potential HGT, gene expression, and phylogeny of the fungal host acterium . Stable acterium .Ampelomyces quisqualis (Ascomycota) during the colonization of its host Podosphaera xanthii (Ascomycota) [G. margarita has also been used to investigate potential modulation of mycovirus diversity as a result of bacterial presence in the endohyphal microbiome [In addition to beneficial symbiotic partnerships, other endohyphal microbiome constituents such as viruses or parasitic fungi can modulate fungal host function. Transcriptomic analyses were used to identify the molecular changes of the mycoparasite omycota) . Mycoviromycota) . Recent omycota) , 48. Tracrobiome . Transcrcrobiome –52.While multi-omics techniques have advanced current knowledge on the diversity and impacts of the broader endohyphal microbiome, many of these studies focus on individual microbiome members. Due to the demonstrated utility of multi-omics and the growing recognition of the complexity of the endohyphal microbiome, we suggest the routine use of multi-omics in examining the full diversity of endohyphal microbiome composition and function over time. To initiate these more complex studies, it is necessary to identify and work to overcome the current limitations of these methods when applied to investigations of small-scale microbiomes.The physical isolation of holobionts from their environments enables small-scale investigations without concerns of contributions from the larger microbiomes. The ability to isolate a fungal host in culture reduces or eliminates external contamination and unassociated genetic and molecular signals, permitting high-resolution investigations of the endohyphal microbiome . HoweverMycoavidus cysteinexigens which relies on its host for production of cysteine [When endohyphal microbiome constituents are separated from their fungal host and the rest of the microbiome, multi-omic analyses can be more straightforward and can result in higher quality data , 55. Howcysteine , 56. Addcysteine , 27. ThiFor sequence-based interrogations, the nucleic acid extraction method can impact extraction efficiency of the endohyphal microbiome. This is partly due to differences in cell lysis requirements for host fungi and their microbiome constituents. Extraction kits for various microbiomes can differentially affect results, particularly in regards to nucleic acid recovery and quality , 58. To Metabolite and bottom-up protein extraction methods and purification efficiency can also vary for small-scale microbiomes. The selection of cellular disruption  and metabolome or proteome extraction methods must be consistent with the platform used for data generation, and different methods can bias results or impact biomolecule recovery , 63. ProSampling methods for extractions must also be considered when working with diverse fungal isolates. Filamentous fungi can vary substantially in their growth rates and hyphal division and production. All of these factors can impact the endohyphal microbiome, as microbiome constituents may replicate and disperse at different rates, creating differences in abundance across older and younger hyphae or hyphal segments. Certain members of the endohyphal microbiome may be present at very low levels, and not all members of the microbiome will have even distributions throughout the host’s hyphal network. Partial sampling of the fungal host, as opposed to collecting all available hyphae, could result in differential capture of microbiome components. Multiple extractions from total cultured fungal biomass or large portions of biomass at multiple locations across the hyphal network may be required to capture the diversity of heterogeneously distributed microbiome features. Spatiotemporal dynamics are important to consider as expression of transcripts, proteins, and metabolites will fluctuate on different time scales and differentially across individual hyphae. This can result in highly variable technical extraction replicates due to inconsistent capture of endohyphal constituent signatures. No extraction methods currently exist for the simultaneous extraction of DNA, RNA, proteins, and metabolites, making it important to consider splitting and preserving samples for each omic type. One of the biggest remaining challenges associated with performing multi-omics on the endohyphal microbiome is the consistently low yield of biomolecules produced by the microbiome constituents relative to the fungal host, which can be a significant hurdle for downstream multi-omics sample processing if the target signal is simply insufficient to provide robust or significant results. Figure Some considerations for the endohyphal microbiome sample preparation stage are relevant for all omics types, such as the consistent challenge of low input of molecular targets from the microbiome, compared with the overwhelming molecular targets from the fungal host. For investigations of nucleic acids, this challenge can be addressed through sequence enrichment, host depletion, and/or target amplification. Amplification techniques are the most straightforward and cost-effective of these options, as many primer options exist that will generally target barcode sequences for identification and taxonomic classification of bacteria/cyanobacteria (16S rRNA gene), viruses , fungi , and algae (18S rRNA gene). The use of these somewhat “universal” primers also means there is no reliance on prior knowledge of the specific diversity of endohyphal microbiome constituents, and this type of analysis provides a general overview of the community profile of the endohyphal microbiome. However, this can require multiple sample preparations with multiple amplification steps which can introduce additional biases and noise, and the results will not provide any genomic information outside of these barcode sequences. Whole genome or whole transcriptome amplification (WGA or WTA) methods can also be used to amplify more than the standard amplicon barcode regions. While newer methods have minimized biases (e.g. GC content biases), chimera generation, and artifacts that can result from these protocols, these issues are still observed to occur and can significantly affect mixed community samples .Alternatively, enrichment and/or depletion assays can be performed. Hybridization-based genomic enrichment strategies have been used in microbiome research to select for known sequences based on lineage-specific signatures from organisms of interest . HoweverFor fungal transcriptome investigations, it is common to deplete rRNAs or to perform polyA selection, as total RNA extractions are dominated by fungal host rRNAs . PolyA sSimilar to nucleic acids, proteins and metabolites produced by the fungal host will be much more prevalent than biomolecules from endohyphal microbiome constituents. Compared with nucleic acids, proteins and metabolites cannot be amplified in a similar manner, but differences in the physical and chemical properties, including charge, hydrophobicity, and molecular weight, of biomolecules of interest  can be exploited for selective enrichment. Recent advances in enrichment for single-cell omics show promise for improving the detection of low abundance analytes from endohyphal microbiomes. Capillary electrophoresis (CE) is commonly used for low input metabolite and protein selection (for bottom-up proteomics) based on biomolecule size and charge , 81. WhiThe generation of sequencing data from endohyphal microbiome samples has unique considerations depending on the input sample type and research goals. Given the challenges listed above, metagenomic sequencing of a total fungal culture extract will often require deep sequencing to adequately assess the total diversity of the endohyphal microbiome. Deep sequencing can be very cost prohibitive, and most of the sequenced reads will belong to the fungal host. Rare members of the endohyphal microbiome may be captured at very low levels or not at all. Microbiome-enriched and/or fungal host-depleted metagenomic samples will reduce this need for ultra-deep sequencing. However, eukaryotic members of the endohyphal microbiome such as algae and other fungi can have much larger genomes compared to other members of the microbiome and require sufficient sequencing depth to acquire adequate genomic coverage.The use of either short- or long-read sequencing technologies is also important to consider. Library preparation kits for short-read sequencing platforms generally require less sample input amounts than long-read platforms. However, single-cell/low-input library kits and workflows currently exist for both platforms for DNA, while only short-read platforms offer similar options for RNA samples. Short-read platforms are more commonly used for microbiome analyses, as their higher average sequencing depths and per-sample read counts are often superior for capturing rare microbiome members . HoweverSelection of an instrument or technique for performing metabolomic and proteomic analyses comes with its own set of challenges, as this requires considering methods best suited for investigating fungal hosts, microbiomes, and/or low-input  samples. Untargeted methods for both metabolomics and proteomics capture the most analyte diversity and capture unknown or undefined biomolecules produced by the fungal holobiont . TechniqMatrix-assisted laser desorption/ionization MS (MALDI-MS), secondary ion MS (SIMS), and electrospray ionization MS (ESI–MS) are currently some of the most popular low-input or single-cell metabolite and protein analysis platforms . MALDI-MOmics techniques that also incorporate an imaging aspect can be critical contributions to investigations of microbiomes, including the endohyphal microbiome. Importantly, microscopy techniques are some of the best methods for distinguishing between members of the endohyphal and epihyphal communities. Imaging techniques also provide insights regarding the spatial heterogeneity within the fungal host and can be utilized to understand where biomolecules originate and end up within the fungal holobiont. Probes for fluorescence in situ hybridization (FISH) are traditionally designed from genomic and transcriptomic sequencing data. FISH imaging has been widely utilized for localization of endohyphal bacteria, and the technique could be expanded for the simultaneous detection and visualization of multiple members of the endohyphal microbiome , 97. SinMALDI-MS can include an imaging aspect, which has even been used for 3D imaging within these small physical scales . RecentlObtaining genome sequences for members of the endohyphal microbiome is often the first step in multi-omics data analysis. These sequences serve as a reference for transcriptomics and proteomics and provide information on taxonomic diversity and functional potential, such as the presence or absence of metabolic pathways, within the endohyphal microbiome. If members of the endohyphal microbiome can be separated from the fungal host through filtration or centrifugation and sequenced individually, the genomic sequencing datasets from each individual can be analyzed using bioinformatic tools and/or pipelines tailored to their specific taxonomy . In cases where separation is not possible, metagenomic sequencing of endohyphal microbiomes will result in mixed datasets containing sequences from all members at variable coverage, with lower abundance constituents having the least amount of sequence coverage. Sequences from metagenomic datasets can be assembled, taxonomically classified, and assessed for quality using a number of established and taxa-specific approaches , 105. ToGenome assemblies can be especially difficult for endohyphal bacteria due to their aforementioned rapid rates of evolution, divergence from available bacterial references, and the possible presence of multiple closely related populations within a single fungal host , 32, 112Trinity software can make transcriptomic analysis without reference genomes more feasible [Trinity has been successfully utilized for de novo assemblies of transcriptomes and metatranscriptomes containing signatures from multiple kingdoms [Adequate genome references are a traditional cornerstone for integrative multi-omics. Incomplete or low-quality reference genome assemblies can make it challenging to utilize transcriptomic analysis software and methods that rely on reference genomes. Tools for de novo transcriptome assembly such as the feasible . Trinitykingdoms –116. Othkingdoms . Assemblkingdoms . ImportaProteomic analyses also heavily rely on adequate host genome and microbiome metagenome reference data. When targeting microbial consortia, and particularly poorly explored ones such as the endohyphal microbiome, it is common practice to construct a protein reference database from annotated assemblies generated from the community’s metagenomic and occasionally metatranscriptomic data. As discussed in previous sections, metagenomic analyses will often not capture complete genomes for all members of the endohyphal microbiome. To ensure a more complete taxonomic and/or functional assignment of proteomic data, reference genomes from similar taxa to those in the microbiome can be used as a substitute, or recently developed de novo peptide prediction methods can be employed. The use of reference genomes of species similar to those found in the microbiome may not adequately represent the expressed proteins which can lead to incorrect or uninterpretable results, and this method can be especially problematic when assessing rapidly evolving bacterial endosymbionts whose proteins may share very little homology with otherwise closely related taxa. De novo methods for proteomic sequence data analysis may be required, although these are relatively new and lack standardization in the field , 120.Analysis of untargeted metabolomics data can be completed without genomic or metagenomic references; however, unique challenges remain. These untargeted analyses rely on databases for accurate metabolite identification against libraries of known metabolites. However, these databases are known to be largely incomplete, thus leading to large proportions of untargeted metabolomics data having “unknown” classifications . Many daMulti-omics-based studies are highly complementary, as examinations of the metabolome and proteome indicate changes in function, but genome and transcriptome investigations help reveal the genes and functional potential responsible for these changes. The combination of multiple omics types, and integration of the data, provides clearer interpretations and conclusions regarding the functions within the endohyphal microbiome and their impacts on the fungal host. Omics techniques and data generation have advanced tremendously in the past decade but still vary in their sensitivity and limits of detection. The utilization of multiple omics types helps to overcome the deficiencies of any single technique, and this approach is often required to determine the impacts of the endohyphal microbiome on the fungal host, as altered expression of biomolecules within the endohyphal microbiome can directly impact gene expression or functions of the fungal host. The process of multi-omic data integration still lacks optimization and standardization, although several tools and workflows exist which have been previously discussed and compared , 124.Research into small-scale microbiomes and microorganism holobionts will require additional efforts towards new and optimized algorithms, bioinformatic tools and workflows, and standardization specifically centered around analyses of low-yield interkingdom samples. There has been a very active campaign towards increased standardization in multi-omics bioinformatics workflows; however, significant shortcomings and gaps remain, particularly for microbial community analyses, making it difficult for many researchers to easily perform end-to-end multi-omic analyses , 125. CuMany advances have been made in integrative multi-omic approaches for investigations into certain members of the endohyphal microbiome. However, significant challenges still remain at each experimental and analytical step that prevent fungal holobionts and other small-scale microbiomes from being routinely and holistically investigated. Integrative multi-omics is challenging even with abounding sample inputs into each omic analysis and with high-quality genome assemblies, and the challenges associated with integrative multi-omics are greatly compounded as additional members of the endohyphal microbiome are simultaneously interrogated and as additional omics types are integrated. The concept of a complex endohyphal microbiome is still relatively new, and the total taxonomic and functional diversity of the endohyphal microbiome has yet to be uncovered. Multi-omics has the potential to vastly expand these investigations, but it is imperative that the microbiome field considers the importance of these microbial holobionts and small-scale microbiomes when designing and advocating for new tools, methods, techniques, and standards. Understanding the functional contributions of each individual microbiome to their respective hosts as well as to larger microbial communities will unlock new opportunities and scientific questions in the field of microbiome research.


In the expanding landscape of metamaterial design, Zheng and colleagues introduces a framework that bridges design and properties, using machine learning to enhance truss metamaterials. A neural network creates an interpretable, low-dimensional space, empowering designers to tailor mechanical properties. Optimisation tasks in the inverse design of metamaterials with machine learning were limited due to the representations of generative models. Here the author comments a recent publication in Nature Communications which generates a latent space representation that unlocks non-linear optimisations. This breakthrough has unlocked a realm of extraordinary functionalities that include counterintuitive negative compressibility2, negative Poisson’s ratios3, mechanical cloaking4, extreme energy absorption5, and guided acoustic waves6. Amidst this array of design possibilities, truss metamaterials, characterized by periodic lattices of beam networks, have emerged as central players. Their appeal lies in their ultralow relative-density strength and ease of manufacturability, yet their full potential remains largely untapped.The ever expanding landscape of metamaterial design has experienced a significant breakthrough thanks to the emergence and continuous development of additive manufacturing, allowing for the creation of cellular solids with intricately tailored microstructural architectures7.Truss metamaterials offer an enticing landscape for innovation with their versatile design space based on lattice topology and geometric attributes. However, this richness has often been limited to a handful of ad-hoc lattices discovered through intuition and trial-and-error. The quest for optimal truss designs faces hurdles due to the computational complexity of exploring the vast and noisy search space. Traditional solutions, including heuristic search strategies, struggle to scale. Even recent efforts to categorize truss lattices akin to molecular structures have grappled with the challenge of discontinuous design spaces9. While most prior work has translated lattices into graphs and tackled the forward problem of predicting property-structure relationships, a recent article titled “Unifying the design space of truss metamaterials by generative modelling” by Zheng10 and colleagues introduces a very creative machine learning (ML) framework. This framework constructs a low-dimensional, continuous latent representation of graph data, effectively bringing together an extensive range of metamaterial designs. This achievement is realized through a neural network architecture, specifically a variational autoencoder, which creates an informational bottleneck, enabling compression of the high-dimensional graph representation into a finite, low-dimensional, and smooth vector representation. This latent space facilitates the generation of lattice designs through random sampling, encapsulating truss connectivity, node positions, and shared information in distinct dimensions, thereby providing comprehensible insight into a previously enigmatic design space.Recent research has harnessed graph representations to interpret trusses as data structures resembling 3D nodal coordinates and connectivity information, akin to moleculesHistorically, the exploration of structure-property relationships in metamaterials has followed a forward trajectory, which is, given a design, effective properties are derived through computational or experimental characterization. In contrast, the inverse challenge—identifying a material design that meets specific mechanical property requirements—has often relied on inefficient trial and error or researchers’ intuition. This has underscored the need for ML methods to expedite the design process and efficiently uncover metamaterials with tailored properties.The challenge of inverse design is particularly compounded by the absence of a standardized design parameterization. Most truss lattices are based on recognizable topologies such as the diamond, Kagome, octahedron, or honeycomb lattices. However, these topologies are labelled in an ad-hoc manner, lacking consistent and rigorous design conventions that can be applied uniformly across different lattice types. Each of these topologies can be defined using a manually crafted finite set of design parameters, such as strut lengths and orientations. Regrettably, these parameters cannot be generalized effectively to encompass other lattice topologies. For instance, while the distinction between the Kagome and octahedron topologies is clear to human observers, it does not possess direct cognitive relevance to a computer algorithm striving to optimize the design. As a result, most existing design optimization methods for truss lattices have concentrated solely on a limited selection of topologies. This approach yields suboptimal solutions and neglects the full spectrum of potential lattice structures available. Hence, the pressing need for a method that can harmonize the design space of truss metamaterials.Towards this end, Zheng and colleagues reduced the discrete design space of lattice parameters to continuous space of latent variables of the autoencoder. This technique, which is central in nonlinear model order reduction methods, is now utilized to distil the underlying manifold of the lattice structures and their mechanical behaviour. However, the latent space suffers from the issue that the reduced variables are not interpretable in general, which leads to a challenge to understand the relationship between latent spaces with physical attributes. The creativity of the authors lies in their ability to decompose the latent space in physically distinct topology-specific, geometry-specific and their shared dimensions. While topology-specific dimensions embed information about connectivity of truss structures, geometry-specific dimensions characterize strut length, diameter. The ability to independently change topology or geometry introduces a modularity in design that is absent in existing optimization techniques. The practical implication of the decomposition is significant as well since it can empower designers to understand the design process and make an informed decision to cater to specific design goals. Beyond human interpretability, the decomposition also improves ability of the framework to generalize to domains absent in training samples.The integration of the ML framework with gradient-based optimization has yielded fruitful results. The framework has been used to design graph-based truss lattices for metamaterials, tailoring mechanical properties across linear and notably nonlinear regimes. This includes designs with exceptional stiffness, auxetic behaviour, and tailored stress–strain responses. The interpretable latent space allows separate or combined adjustments to topology and geometry, offering designers a remarkable degree of control. The unified latent space extrapolates creatively, enabling the discovery of lattice designs far beyond the known design and data space, achieving stiffness, auxetic behaviour, and unique stress-strain characteristics.The framework proposed by Zheng and team stands out in its ability to spark creativity. Analogous to an artist’s palette, the latent space empowers effortless generation of truss structures through elegant operations—sampling around familiar data points, traversing latent axes, and seamlessly interpolating between two points. In contrast to conventional methods that often obscure physical insights, the neural network architecture of this framework bridges the gap by predicting truss properties from the latent space. This fusion of generative modelling and predictive analysis equips researchers to explore uncharted territories and unveil designs that defy convention.Zheng and colleagues’ framework has combined the topological characterization and mechanical response in a modular fashion, which enables them to obtain optimized lattice structures for linear or nonlinear stress-strain behaviour in rather ease Fig. . Extensi11. In the recent work by Zheng and colleagues, the scope of considered topologies is confined to cubic symmetry. However, there exists room to broaden this scope, encompassing highly anisotropic lattice designs. Furthermore, the material properties need not adhere to linearity; instead, they can span a spectrum from hyperplastic polymers to metal plasticity12, thereby introducing another layer of non-linearity into the design process.Numerous unanswered questions and unexplored territories persist in the realm of metamaterial design. Firstly, the acquisition of experimental data remains imperative for comprehending how the simulated behaviour of intricate metamaterials aligns with their actual performance. Additionally, the incorporation of imperfections in additively printed metamaterials into a machine learning framework can shed light on their impact on mechanical performance


Head and neck cancers (HNCs) are a group of cancers that affect parts like the mouth, throat, and glands in the neck. These cancers are quite complex and can be challenging to detect and treat early. Microfluidic devices are miniature chips that use a small volume of biological samples and have helped in understanding these cancers better. They have revolutionized the way we diagnose and treat cancer. These devices have also allowed us to create models of individual patients’ cancers on a chip, which help develop personalized treatments. In this review, we will talk about how microfluidics has improved the screening of drugs for treating HNC and how it helps in detecting cancer early and in understanding how treatments work. We will also discuss the challenges we face in using these microfluidic technologies in real-life medical settings.Head and neck cancers (HNCs) account for ~4% of all cancers in North America and encompass cancers affecting the oral cavity, pharynx, larynx, sinuses, nasal cavity, and salivary glands. The anatomical complexity of the head and neck region, characterized by highly perfused and innervated structures, presents challenges in the early diagnosis and treatment of these cancers. The utilization of sub-microliter volumes and the unique phenomenon associated with microscale fluid dynamics have facilitated the development of microfluidic platforms for studying complex biological systems. The advent of on-chip microfluidics has significantly impacted the diagnosis and treatment strategies of HNC. Sensor-based microfluidics and point-of-care devices have improved the detection and monitoring of cancer biomarkers using biological specimens like saliva, urine, blood, and serum. Additionally, tumor-on-a-chip platforms have allowed the creation of patient-specific cancer models on a chip, enabling the development of personalized treatments through high-throughput screening of drugs. In this review, we first focus on how microfluidics enable the development of an enhanced, functional drug screening process for targeted treatment in HNCs. We then discuss current advances in microfluidic platforms for biomarker sensing and early detection, followed by on-chip modeling of HNC to evaluate treatment response. Finally, we address the practical challenges that hinder the clinical translation of these microfluidic advances. Head and neck cancers (HNCs) represent a heterogenous group of tumors originating from the head and neck regions which comprise the upper aerodigestive tract . Even wiCurrent treatment strategies for HNCs include complex treatment regimens delivered by multidisciplinary teams. Surgical resection and radiotherapy (RT) forms the basis of primary treatment and have shown satisfactory outcomes A,B 13]..13]. HowSupported by the advances in material biology, cell culture techniques, and functional assays, researchers have transitioned from the conventional 2D  systems to study cancer biology. These advances shed light into a plethora of investigations on cancer microenvironment or tumor microenvironment (TME) by utilizing 3D  tissue cultures including co-culture systems ,21,22. BDeveloping sophisticated primary cell-based 3D models for studying the TME is a complex task. However, the challenge lies in utilizing these models for large-scale screening under various parameters, as limited sample availability and a lack of precise control over cell–cell and cell–stromal interactions make it difficult to achieve. Some of these challenges can be overcome by utilizing the rapidly emerging field of microfluidics. Microfluidics is an interdisciplinary field focused on manipulating and controlling small volumes of fluids in microscale channels and chambers comparable to biological cells and microorganisms ,33. Its Microfluidics has emerged as a promising technology in cancer research and therapy, offering unique opportunities to improve diagnostics, understand tumor biology, and develop personalized treatment strategies ,37,38. TIn this review, we first describe the scope of microfluidics in precision oncology with a focus on HNCs and discuss their potential in allowing early diagnosis and for high content/throughput screening applications. Next, we discuss the current advances in microfluidic platforms for diagnosis and detection of HNCs with a focus on circulating tumor cells (CTCs) and cancer biomarkers. We then delve into the recent advances in microfluidics in HNC tumor-on-chip platforms for studying therapeutic responses. Finally, we conclude by discussing the challenges in translating these microfluidic proof-of-concept approaches into a clinical setting and provide recommendations for future research.Analogous to the notion “one size fits none”, commonly used in the clothing industry, treating cancer using an “all purpose” approach has become obsolete. The ideology of precision medicine surfaced over two decades ago with a principle of understanding the molecular alterations in a patient’s tumor to administer agents that target these changes to improve the clinical management of cancer. Primary studies on these alterations were mostly measured as genomic mutations, which were used as targets to treat and predict patient outcomes . HoweverFostered by the advances in high-resolution assays such as single-cell RNA and DNA sequencing, spatial transcriptomics, mass cytometry, metabolomics etc., we can now achieve a significant understanding of the evolving molecular map of heterogenous cancer cells to find potential targets and therapies ,51. To aCombining functional assays with capabilities of single-cell analysis when performed under physiologically relevant culture conditions opens major avenues in precision oncology. Nevertheless, even with the advances in functional readouts and sequencing technologies, challenges exist in terms of enriched isolation, relevant culture, and maintenance of cancer tissues and cells. The feasibility of using cancer cell lines or primary cells under 2D culture conditions is compelled by their ease, low cost, and high-throughput nature. However, these conditions barely recapitulate the complex TME, especially their multicellular nature and supporting stroma—which is highly sensitive to external physico-chemical and mechanical cues.Microfluidic platforms possess the ability to bypass many of these challenges and enable the development of highly relevant models, representative of in vivo conditions to facilitate precision therapy. First, microfluidic channels utilize sub-micron liter sample volumes, which makes it easier to run multiple, comprehensive analyses when there is a shortage of relevant sample type  DNAs). On-chip platforms such as Parsortrix  and CTC-–1, enabling the simultaneous measurement of interleukin 6 (IL-6), IL-8, vascular endothelial growth factor (VEGF), and VEGF-C proteins in diluted serum [Another advantage of using microfluidic technology is their versatility as POC devices. A POC test (POCT) is a simple, portable, miniaturized device used for analysis, detection, and/or screening of medical conditions in real time . These ded serum . More reed serum . Similared serum ,63,64,65ed serum ,67. Commed serum . Enzyme-ed serum ,70. Detaed serum ,69. NeveThe second advantage of using a microfluidic approach towards precision therapy is the possibility of compartmentalization for cancer cell culture. Multichannel microfluidic chips act as effective co-culture systems and allow independent culture of different cell types promoting cell–cell crosstalk. Such culture systems can be established with precise spatio-temporal control and continual circulation aiding in both mechanotransduction  and delivery of signaling cues . Additionally, depending on the fabrication method, microfluidic devices allow precise control over molecular diffusion of chemotactic agents and study cellular migration including vascular biology . This unFunctional assays, when used in combination with microfluidic models, provide not only high physiological relevance, but hold the multiplexing potential to test hundreds of drugs or small molecules in conjunction with several patient samples at desired complexity. A schematic proposal of utilizing a microfluidic workflow for precision medicine is shown in In parallel, liquid biopsy samples can be used to isolate CTCs, cell-free ctDNA, miRNA, extracellular vesicles (EVs), and exosomes using previously described on-chip platforms to detect, isolate, and enrich CTCs. These CTCs, even when obtained in small quantities, can be incorporated into the 2D/3D culture workflows and subjected to targeted panel sequencing approaches . Cell-frHow cancer is treated has become a significant driving force of the current technological innovation ranging from nanotechnology, radiosurgery, immunotherapy, and many more . HoweverBiomarkers play a crucial role in the early diagnosis of HNCs, as they are specific molecules or indicators that can be detected in various body fluids or tissues, indicating the presence of cancerous or precancerous lesions. Early detection of HNCs is vital for improving treatment outcomes and patient survival rates. Combining microfluidic assays with known biomarkers of HNCs allows for routine screening and early diagnosis in high-risk populations. The rise in HPV-related oral cancer indicates that viral infection is a significant risk factor for certain HNCs, particularly oropharyngeal cancers. Detecting HPV DNA in tumor samples or oral swabs can aid in identifying high-risk patients . The tuml-phenylalanine, and S-carboxymethyl-l-cysteine which show potential for high diagnosis accuracy [RASSF1A, DAPK1, p16) [Salivary biomarkers such as matrix metalloproteinases (MMPs), cytokines, and microRNAs, have shown promise for early detection of HNCs, as saliva can be collected non-invasively . A systeaccuracy . DetectiK1, p16) . Small nK1, p16) . While bA liquid biopsy approach allows for a non-invasive and accessible screening method for HNC and it can also provide sample repeatability and real-time monitoring at an inexpensive cost ,103. In Microfluidic technologies have become a key proponent in mimicking the complex TME as an in vitro 3D model addressing many challenges faced by existing technologies in the screening and detection of HNC ,131. MicMany studies have elucidated many key findings and the efficacy of microfluidic systems in screening and detecting key biomarkers for HNC. Microfluidic systems still have yet to be used in a clinical setting but there has been tremendous groundwork made in developing novel screening and detection methods . One sucAnother important aspect of microfluidic technology is the ability to reduce the overall cost while maintaining accuracy in the screening of HNC in its early stages. Zoupanou and colleagues took an alternative approach by investigating a low-cost microfluidic device, SMILE, for the early screening of oral squamous cell carcinoma . Their SOvercoming the challenge of increasing the sensitivity and specificity of microfluidic technology with regard to the screening and detection of key biomarkers of HNC requires a large testing sample population to reliably translate these techniques into a clinical setting . High-thAs the technology of microfluidic devices improves drastically in the early screening of key biomarkers for HNC, it will be important to combine the use of AI as it can aid in the real-time analysis, provide immediate feedback, and also improve accuracy with the help of specifically designed algorithms that can be trained on large sets of patient data to allow microfluidic devices in detecting specific biomarkers for specific cancers. Additionally, existing isolating and capturing of key biomarkers along with low-cost and consistent fabrication methods of microfluidic devices will be a required step in the practice of personalized medicine.As previously discussed, the treatment of HNCs typically involves the implementation of conventional methods such as surgery, chemotherapy, and RT. These modalities have demonstrated their efficacy, particularly when administered during the initial stages of the disease before significant progression occurs. However, it is important to note that individual patients exhibit varying responses to these treatments, posing a challenge in developing a universally applicable approach. Given the unique nature of HNC, which necessitates a heightened level of accuracy and precision, the integration of microfluidic chip platforms has emerged as a promising avenue for enhancing the effectiveness of cancer treatment interventions. The utilization of these platforms allows for the prediction of treatment responses, ultimately contributing to more efficient applications in the management of cancer.In a move toward personalized medicine, maintenance of tumor biopsies in microfluidic tissue culture devices are being developed. Bower et al. reported a microfluidic culture system that successfully maintained HNSCC tissues for 48 h, and the culture system allows testing of different treatment modalities with response monitoring  system that enabled high-throughput analysis of tissue microarray and the response to different treatment modalities. Using the patterns of biomarker barcodes, which consist of a series of expressed linear patterns of specific biomarkers. A multichannel PDMS microfluidic device was reversibly assembled on each core of cell microarray (CMA) section slides. By injecting primary antibodies from different biomarkers independently into each channel, multiplexed immunostaining can be performed on each core of the CMA. The study confirmed that this system, which has been verified by performing multiplexed microfluidic IHC on CMA samples, provides high reproducibility and the potential for high-throughput analysis with molecular diagnostic capability .RT involves using focused radiation to cause nuclear damage to the tumor cells. The extent of nuclear damage to the cells helps to trigger apoptosis leading to the death of the tumor cells. Irradiation damages the DNA within the tumor cells, preventing further replication and triggering cell death. The biocompatible and physical properties of microfluidic chips allow the analysis of tumor cells and their response to different doses of radiation. Carr et al. used a double-layered glass microfluidic device with one inlet and two outlets to maintain HNSCC samples from 35 patients and tested different radiation doses between 2 Gy and 40 Gy to evaluate cell death using levels of lactate dehydrogenase (LDH) and cleaved cytokeratin 18 (cCK18) . They shMore recently, to improve consistency in radiation dose delivery, Kennedy et al. described a microchip assay to optimize the amount of radiation exposure during RT. In their study, each tumor-on-a-chip platform is composed of two identical parts with central axial threaded holes to secure the radiation tubing to the system via coned adaptors  chip method . The MDTIn conclusion, tumor-on-chip microfluidic platforms and functional assays are a valuable tool in the preclinical, in vitro, and ex vivo modeling of HNCs. They offer improved sensitivity, precision, and the ability to analyze small sample volumes and enable testing of multiple drug combinations to evaluate dynamic changes in patient samples in response to treatments. These assays have the potential to improve patient outcomes by enabling early detection, accurate monitoring, and predict personalized treatment strategies.Traditionally, cancer is often diagnosed through biopsy and the histological evaluation that follows, which could be invasive, risky, and expensive. On the other hand, the use of chips with microfluidic properties allows use of “liquid biopsies”, where blood samples are analyzed for proteins, exosomes, vesicles, and CTCs present in the bloodstream that have broken off from the main tumor/metastasis tumor . These pMoreover, these chips could automate some processes found in traditional biopsy diagnostic techniques and hence have a smaller requirement in terms of labor intensity and trained technicians as opposed to the biopsy and the IHC that often follows . These oTranslating these aforementioned methods to clinic, however, has its own challenges. CTCs, exosomes, extracellular vesicles, as well as other proteins that are present in the patient’s bloodstream and are associated with the tumor in question, are hard to isolate from human peripheral blood since there are a lot of other entities that have a similar size as the target proteins and cells . Thus, fThe lack of standardized chip design is a prevalent issue in the field of microfluidics, particularly in the context of lab-on-a-chip systems for cancer diagnosis and treatment. Many studies have developed customized devices based on their specific experimental needs, which limits compatibility and interchangeability between different applications and experimental setups. This lack of standardization hampers the validation and transferability of results across different study settings. To improve efficiency and streamline processes, it is important to establish standardized practices for microfluidic chip fabrication, design, and usage. Without such standardization, operating different chips under varying experimental conditions becomes challenging, requiring repeated optimization and extensive personnel training. Additionally, the lack of communication among academic groups specializing in chip development further limits the scalability of innovative devices emerging from different institutes. Furthermore, the relative novelty of microfluidic lab and tumor-on-a-chip devices means that there are limited individuals trained or equipped to develop and apply these devices.Efforts should focus on developing a versatile pipeline for microfluidic device design that minimizes training requirements and overcomes physical constraints. Several microfluidic startups and biotechnology firms offer prefabricated, custom-made on-chip devices for different organ systems. Such systems can be designed to iteratively accustom to different cell types and once optimized, are assay-specific. Academic research groups can collaborate with companies to scale up the fabrication of already optimized microfluidic devices and create marketing pipelines to make the technology readily available to more researchers. Collaboration between clinical cancer centers that have routine access to cancer biopsies and research laboratories is crucial and can lead to the identification of novel targets and biomarkers. This association can be extended to industrial research and development teams who can design clinical-grade, biomarker-specific, microfluidic assays and POC devices.Another challenge with the use of microfluidic devices in analyzing patient samples is the accompanying ethical and regulatory concerns . FirstlyThe complex and aggressive portrait of HNCs has led to high morbidity and poor survivability among patients. Microfluidic technologies have shown the potential in replicating the in vivo TME for HNCs, especially aggressive forms like HNSCC, enabling early diagnosis and therapeutic evaluation. Microfluidic technology accurately represents the complexity of tumors by controlling physical and chemical cues in microarchitecture. It integrates well with various sensing and detection methods, making it suitable for early cancer detection, high-throughput screening, and studying the mechanisms of anticancer treatments. Utilizing microfluidic technology to preserve patient biopsies presents a potential alternative to animal models that is not only cost-effective but also easily scalable and user-friendly. These advancements hold the promise of improving scientific research by employing human tissue to better represent human diseases, thereby facilitating more accurate and relevant findings in the future. However, despite the potential, microfluidic technologies are still in the early stages, and further validation through comparison with in vivo results is necessary before clinical implementation. For example, targets and hits identified from the testing of hundreds of drugs using high-throughput microfluidic platforms should be replicated using multiple patient-derived cell lines or cell models. These drug interactions should be further validated for in vitro generalizability by multi-user groups. The most confident hits and targets should then be studied further using in vivo models to confirm their clinical relevance. Such a sequential approach to validation using microfluidic approaches would reduce time-consuming animal studies to screen a large number of drug candidates, and allows a quicker translation to clinics.Currently, most cancer-on-chip research primarily focuses on demonstrating the capability of microfluidic devices to measure specific analytes  in the cells and tissues or after different forms of treatments . These studies are often led by biologists or engineers, each approaching the question from their respective disciplines, and they have shown the feasibility of studying individual parameters. However, integrating these parameters to address broader questions such as point-of-care and personalized medicine or evaluating off-target effects of treatments in other organ systems has not yet been fully achieved. There is a need for long-term investment and collaboration among multidisciplinary teams in academia and industry to fulfill the innate potential of microfluidics for successful translation from preclinical findings to clinical decision-making in cancer diagnosis and treatment.


While some older adults retain physical and mental capabilities comparable to individuals that are decades younger, others may be incapable of self-care. Understanding the factors that determine where an individual will find themselves on this spectrum, particularly those that may be modifiable, is therefore critical. In pursuit of this goal, the current Research Topic focussed specifically on how changes within the brain contribute to both healthy and pathological aging.Yan et al. assessed how age-related changes in WM contribute to the ability of older adults to perceive global motion. This study used diffusion tensor imaging (DTI) to identify several specific white matter tracts where age-related reductions in integrity predicted reduced global motion perception. This was suggested to support the “disconnection hypothesis” of cognitive aging. Using a slightly different approach, Du et al. instead leveraged magnetic resonance histology  integrity are one example that has been suggested to underpin many age-related functional deficits  to report a number of deficits having a complex relationship with reduced performance in a dual-task walking paradigm. In contrast, Vaughan et al. instead utilized machine-learning to quantify how an individual's chronological age differed from their brain-predicted age (as an indicator of accelerated or decelerated brain aging). They then demonstrated that accelerated brain aging moderated the relationship between leg strength and mobility.While local changes in specific brain structures are clearly important, considering how alterations to multiple structural elements interact to drive brain aging is also critical. To incorporate this, Hicks et al. examined associations between sex steroid hormones and age-network relationships in both males and females, focusing on network segregation. Although network segregation was not associated with hormone levels in females, network segregation in the cerebellar-basal ganglia and salience networks showed a complex relationship with age. Given their role in cognition and balance, it is important to understand how age-related changes in segregation within these networks drive behavior.One important factor often overlooked in studies of brain aging is the large differences in hormones between females and males across the lifespan. To assess the potential influence this may have on brain imaging studies, Greeley et al. investigated how anodal transcranial direct current stimulation (atDCS) over prefrontal cortex influenced sequence learning in older adults. While increased performance was expected, atDCS instead reduced learning, possibly due to the timing of the intervention. These findings add to a growing body of literature demonstrating the need for optimized NIBS interventions in older adults.Modulation of brain activity represents a promising avenue for improving how we age, and one approach to achieving this is to use non-invasive brain stimulation (NIBS). For example, Ma et al. further demonstrates this within the context of AD. This study investigated the therapeutic mechanisms of Cordycepin, a nucleoside adenosine analog derived from traditional Chinese medication that has shown anti-AD properties. Using network pharmacology and molecular docking methods, five genes  potentially serving as targets of Cordyceptin were identified. These in-silico findings provide novel insights for developing optimal treatments for AD.As an alternative example of approaches to brain modulation, acupuncture has shown an ability to modify aberrant activity in patients with mild cognitive impairment (MCI), although the outcomes have been variable. Consequently, the meta-analysis by Ma and colleagues compiled the evidence examining the influence of acupuncture on functional MRI measures in MCI patients. Across studies, acupuncture was found to increase activity within several brain areas, with changes in thalamic areas associated with cognitive function. While supporting the potential utility of acupuncture in MCI, the authors also recognize confirmation is needed from more rigorous RCT studies. However, the outcomes of this study nonetheless demonstrate the potential utility of alternative approaches for influencing the aging brain. The study by Cattaneo et al. validated the “Guttman Cognitest” – a self-administered digital cognitive assessment requiring ~20 minutes – against conventional paper-and-pencil tests in a middle-aged cohort. Principal component analysis revealed three factors consistent between test types , although there was some variance in how specific subtests loaded onto each factor. Furthermore, performance showed the expected negative association with age and positive association with years of education. The authors concluded that this digital assessment is appropriate for measuring cognitive function in large samples of middle-aged adults.While modulating function represents a core aim of many studies in aging neuroscience, assessing function remains a fundamental necessity. However, existing approaches are often time consuming or require specialist clinicians. To address this, Consideration of the neuroanatomical and neurophysiological effects of age is often restricted to the context of the central nervous system (CNS). In contrast, interactions with the systemic environment may also contribute to age-related changes within the brain. For example, inflammation is increased in older adults, which may contribute to age-related cognitive deficits  covering a broad range of topics within the neuroscience of advancing age. This includes important new information about brain imaging, brain modulation, functional assessment, and the interaction between systemic and central factors. On the one hand, the breadth of this collection demonstrates the enormity of the challenge faced by the field. However, on the other hand, it's constellation of insightful approaches demonstrates that this challenge will be faced with enthusiasm.GO drafted the manuscript. All authors critically revised and approved the manuscript.