The landscape of epidemiological research is experiencing a technological transformation, driven by the rapid expansion of big data and advancements in artificial intelligence (AI) and machine learning (ML). This workshop explored the opportunities and challenges associated with integrating diverse data sources into population-based research at different levels, including electronic health records (EHRs), genomic and omics data, imaging, wearable device data, and social determinants of health measures, among others. AI/ML tools present powerful capabilities for analyzing these vast datasets, offering advancements in health risk prediction, disease pattern identification, and the development of personalized interventions. However, the integration of big data introduces technical barriers related to data heterogeneity, privacy and security concerns, and the potential to exacerbate health disparities through algorithmic biases. In September 2023, the National Institutes of Health's (NIH) National Heart, Lung, and Blood Institute (NHLBI), in collaboration with the National Cancer Institute (NCI) and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), hosted a workshop to address these challenges and discuss the integration of big data into epidemiology and population-based studies. Key themes from the workshop emphasized interdisciplinary collaboration, data standardization, and the development of robust ethical frameworks, as well as the importance of advancing data governance, implementing transparent consent processes, and employing privacy-preserving techniques to maintain public trust. Additionally, the workshop highlighted the transformative potential of digital health technologies, such as wearable devices, which, when integrated with EHRs, enhance data granularity, facilitate early disease detection, and strengthen public health surveillance. Ethical, legal, and social issues (ELSI) are central to responsibly leveraging big data and AI in research, unbiased algorithms, the use of diverse datasets in AI training, and continuous human oversight to mitigate risk and ensure validity. The workshop also emphasized the need for workforce training and education in data science and bioinformatics to prepare researchers for utilizing these technologies effectively. The workshop concluded by recognizing the need for a balanced approach that addresses data integration challenges while harnessing AI/ML to improve healthcare outcomes. By fostering interdisciplinary collaboration, prioritizing privacy, and embracing data-driven methodologies, epidemiological research can unlock the full potential of big data to transform public health and clinical practice.
ImportanceTo our knowledge, this represents the first adult-only, fully endoscopic, three-arm comparative cohort of autograft, allograft, and xenograft materials in type I tympanoplasty.ObjectiveTo compare graft-take, audiometric outcomes, operative time, and complications among perichondrium, MegaDerm, and Biodesign in adult endoscopic type I tympanoplasty. Retrospective comparative cohort study. Tertiary referral center. Adults who underwent endoscopic type I tympanoplasty with perichondrium, MegaDerm or Biodesign between October 2021 and March 2025. Patients with revision surgery, concomitant otologic procedures, active middle-ear disease, profound sensorineural hearing loss, preoperative air-bone gap (ABG) ≥50 dB, or follow-up <3 months were excluded.Intervention or ExposuresEndoscopic type I tympanoplasty using perichondrium (autograft), MegaDerm (allograft), or Biodesign (xenograft). Graft-take rate, hearing gain (air-conduction and ABG), operative time, and complications.ResultsNinety-three ears were analyzed (perichondrium n = 33; MegaDerm n = 21; Biodesign n = 39). Three-month graft-take rates were similar, and final graft-take rates remained comparable across groups (3 months: 90.9%, 90.5%, 94.9%; P = .6862; final: 84.8%, 85.7%, 84.6%; P > .999). Air-conduction (AC) and ABG improved significantly within all groups. Between-group differences were not significant for AC gain (13.79 ± 9.84 vs 7.24 ± 12.46 vs 9.14 ± 10.01 dB; P = .0804) or ABG gain (9.58 ± 10.46 vs 8.82 ± 10.37 vs 7.58 ± 8.46 dB; P = .7757); the proportion achieving postoperative ABG ≤20 dB was similar (P = .475). Operative time was significantly longer for perichondrium (98.23 ± 32.35, 68.52 ± 20.84, and 74.88 ± 17.27; P < .0001). Complications were infrequent (otomycosis, n = 3; myringitis, n = 1), and no facial palsy, intractable vertigo, profound sensorineural hearing loss(SNHL), or dysgeusia occurred. In adult endoscopic type I tympanoplasty, perichondrium, MegaDerm, and Biodesign demonstrated comparable short-term graft-take and audiometric outcomes, while commercially available grafts were associated with shorter operative time. These findings support patient-centered graft selection balancing donor-site considerations, operative efficiency, and cost; prospective studies with standardized follow-up and patient-reported outcomes are warranted.
Plant natural products (PNPs) are widely used in pharmaceutical, cosmetic, and food industries. Currently, their commercial supply largely relies on plant extraction, yet, suffers from low yield and limited resources. Synthetic biology provides a promising solution by reconstituting biosynthetic pathways of PNPs in microbial systems. However, unknown enzymatic steps or poor functional performance of plant-derived enzymes often make it particularly challenging for the PNPs production in microorganisms. To address these limitations, much progress has been made in enzyme mining, enzymatic mechanism elucidation, and enzyme optimization by protein design technologies. The deep integration of artificial intelligence and synthetic biology has provided attractive solutions for the sustainable production of PNPs. This review introduces the cutting-edge advances of protein design technologies in PNPs biosynthesis, elaborates on the approaches to resolve the main bottlenecks in PNPs biosynthesis, and discusses the immense application potential driven by the integration of AI and synthetic biology.
The increasing adoption of digital health technologies has amplified the need for robust, interoperable solutions to manage complex healthcare data. We present the Spezi Data Pipeline, an open-source Python toolkit designed to streamline the analysis of digital health data, from secure access and retrieval through processing, visualization, and export. The Pipeline is integrated into the larger Stanford Spezi open-source ecosystem for developing research and translational digital health software systems. Leveraging Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR)-based data representations, the Pipeline enables standardized handling of diverse data types, including sensor-derived observations, electrocardiogram (ECG) recordings, and clinical questionnaires-across research and clinical environments. We detail the modular system architecture and demonstrate its application using real-world data from the Pediatric Apple Watch Study (PAWS) at Stanford University, in which the Pipeline facilitated efficient extraction, transformation, and clinician-driven review of Apple Watch ECG data, supporting annotation and comparative analysis alongside traditional monitors. By reducing the need for bespoke data engineering and enabling prospective, clinician-in-the-loop analysis within standardized workflows, the Spezi Data Pipeline supports reproducible and interoperable clinical research using routinely collected digital health data.
Impact1 at the Stanford Mussallem Center for Biodesign was established in 2019 through its core partnership with UCSF as an FDA-funded Pediatric Device Consortium. We hypothesized that providing innovators in pediatric and maternal healthcare with mentorship, connections to experts, and grant funding would promote development, validation, approval, and commercialization of safe and effective health technologies for pediatric and maternal patients, and lead to positive broader impacts, measured as patients treated, capital raised, and jobs created. Data were collected from 180 innovation teams supported by Impact1 between 2019 and 2024. Sources included intake forms, annual surveys, and public data. Key metrics analyzed included team demographics, innovation stage, resource utilization, funding raised, patients reached, and jobs created. Impact1 supported diverse teams across various stages of development with key resources including coaching, connections to experts, and funding opportunities. Since 2019, supported innovations have collectively treated an estimated 88,000 patients, raised $240 million, and created over 400 jobs. Evidence suggests that Impact1 resources positively influence the trajectory of early-stage medical device development in pediatric and maternal health. Future research will focus on establishing a more robust causal link between program resources and innovation outcomes.
Synthetic nucleic acids are a key input to modern biotechnology, yet they represent dual-use materials that require robust screening to mitigate biosecurity risks. The prevailing screening paradigm, which identifies sequences of concern (SoCs) through sequence similarity to controlled pathogens and toxins, may not fully capture risks posed by AI tools that can decouple biomolecular function from reliance on known sequences. Rapidly advancing biodesign capabilities enable the generation of genes and proteins that might evade sequence-based detection. We highlight the critical need for function-based screening approaches that can detect sequences capable of hazardous biological functions, regardless of similarity to known SoCs. We examine the feasibility of function-based screening with an initial focus on proteins, arguing that, while protein sequence space is vast, biologically functional proteins are significantly constrained by biophysical and biochemical requirements that can be learned and modeled. We propose a concrete implementation framework organized along a continuum of complexity, starting with toxins as the most tractable targets before expanding to more complex pathogenic functions. We then discuss open challenges and describe a research and development strategy to address them.
Given that some DNA viruses have been found to exhibit virus-host co-evolution and establish lifelong infection, mammals with unique evolutionary histories in island ecosystems likely host exceptionally diverse viruses. Madagascar is inhabited by endemic non-human primate and rodent lineages interacting with expansive populations of introduced non-native rodents across the island. Using a viral metagenomic workflow on 189 oral swabs of lemurs and rodents in southeastern Madagascar, we characterized genomic sequences of DNA viruses in the families Adenoviridae, Circoviridae, Orthoherpesviridae, Papillomaviridae, Parvoviridae and Polyomaviridae and assessed their phylogenetic relationships to known viruses. Endemic lemurs and tufted-tailed rats displayed particularly novel DNA viral diversity mirroring the geographic isolation and subsequently rich evolutionary history of their hosts. Notably, we provide the first coding-complete sequences in lemurs of herpesviruses, polyomaviruses, adeno-associated viruses and circoviruses. In contrast, the DNA viral communities of black rats in Madagascar were similar to those found in globally distributed black and brown rat populations, given their broad geographic spread and relatively recent introduction to the island. Given the scarcity of viral research in natural populations of lemurs and rodents in Madagascar despite the island's exceptional biodiversity and escalating anthropogenic pressures, this study provides a genomic and phylogenetic foundation for DNA viruses infecting Malagasy lemurs and rodents.
One of the common issues in the R&D of new drugs is the failure of clinical trials caused by the species-specific inadequacy of animal models to assess drugs' efficiency and safety. Therefore, systems like organ-on-a-chip and, particularly, liver-on-a-chip (LOC) can be an efficient tool for recapitulating in vivo-like human physiology at the microscale. This review focuses on discussing LOC design, emphasizing its architecture and validation to reveal the trends in searching for a balance between biomimetics and functionality. We found that the huge variety of already published models can be divided into five groups based on their configuration complexity: flat one-channel, flat two-channel, vertically stacked multilayered, hexagonal-patterned, and multi-well chips. While researchers attempt to recapitulate the liver's histology and its functions in detail by increasing the complexity of devices' architectonics, industrial companies prefer to promote more simple and flexible solutions. Thus, the LOC designs of the future require neglecting some liver characteristics to make them standardizable and sustainable, which could facilitate their introduction into the market and clinics.
Background: Short sleep and formula feeding during infancy are associated with increased risk of childhood obesity. Feeding practices and sleep arrangements vary during infancy and may also be dynamic, yet their impact on infant night sleep duration remains unclear. Understanding these relationships is crucial for formulating recommendations to support breastfeeding and address sleep concerns. Objective: We examined the association between feeding mode and parent-reported infant night sleep duration during the first postnatal year, while additionally evaluating night-weaning and bedsharing as contextual sleep-related practices. Methods: Infants in the Phoenix Metropolitan Area (n = 193) were followed up at 3, 8, 13, 26, 39, and 52 weeks post-birth. Sleep and feeding questionnaires were answered at each visit. A multilevel growth model estimated infant night sleep duration trajectories by feeding mode (ordinal: exclusive formula, mixed, exclusive breastfeeding), night-weaning, and bedsharing as time-variant predictors. Maternal education and household income were covariates to account for differences in study attrition. Results: Infant night sleep duration followed a curvilinear trajectory, starting at 7.92 h (95% CI: 5.78, 10.06) and increasing by 0.40 h/month (95% CI: 0.21, 0.60), with a deceleration over time (0.02 h/month2, p < 0.001). Each increase in levels of breast milk consumption was associated with an increase in infant night sleep duration (B = 0.87 h, p < 0.001), but the association weakened as the infant aged (B = -0.07 h/month, p < 0.001). Despite 59.7% of bedsharing infants being exclusively breastfed, bedsharing was not significantly associated with infant night sleep duration. Similarly, night-weaning was not significantly associated with infant night sleep duration. Conclusions: Breastfeeding is associated with longer infant night sleep duration, whereas bedsharing showed no association despite its correlation with breastfeeding. This research highlights the importance of breastfeeding in early life, not only for its developmental benefits but also for its relationship with infant night sleep duration, an essential component of healthy infant growth.
Extreme outdoor temperatures are known barriers to physical activity and may constrain life-space mobility, the geographic footprint of where people live, work, and recreate, and an important indicator of health and independence among older adults. We conducted a pilot study to evaluate the feasibility of a mobile health (mHealth) app designed to objectively capture life-space and to demonstrate its utility through a downstream analysis of ambient temperature and life-space mobility. Using data collected via an iPhone app from 82 participants in an ongoing cohort study (June 2023-January 2024), we used linear mixed-effects models to examine associations between daily average temperature and 3 objective life-space measures: ellipse area, maximum distance traveled, and total distance traveled. Models were stratified by season and adjusted for relative humidity and sociodemographic covariates. The app successfully captured high-resolution longitudinal mobility data over 2 weeks per participant. There was a significant negative nonlinear association between higher daily average temperature and life-space in the summer. With the peak life-space ellipse area observed at 28.8 °C, for every degree Celsius greater than 28.8 °C, we found a statistically significant decrease in ellipse area by 2.97 km2 (95% CI: -5.45, -0.51; p = .02). Findings were similar for the outcomes of maximum and total distances traveled. This study demonstrates that mHealth technology is a feasible tool for assessing life-space mobility in older adults. Higher temperatures are associated with lower life-space metrics, highlighting the potential of app-derived metrics as digital biomarkers for mobility research.
Global plastic production surpassed 436 million metric tonnes in 2023, with polyolefins, polyethylene and polypropylene, and polyesters, polyethylene terephthalate and polybutylene adipate terephthalate dominating the persistent fraction. In extreme environments, these recalcitrant polymers accumulate rapidly: hadal-trench sediments contain microplastic abundances of 71.1 items per kilogram dry weight, while bottom waters reach 2.06-13.51 particles per litre. Abiotic degradation is severely limited by hydrostatic pressure, hypersalinity, low temperature, and anaerobiosis. Although bacterial and fungal pathways have received primary attention, archaea adapted to polyextreme conditions represent an underexplored resource. Landmark discoveries include PET46, a lid-containing feruloyl esterase from uncultured Candidatus Bathyarchaeota in Guaymas Basin deep-sea sediments that hydrolyses semi-crystalline polyethylene terephthalate powder at rates comparable to established bacterial PETases while outperforming them on oligomers. Subsequent metagenomic prospecting identified GuaPA, a distinct Bathyarchaeia-derived PETase capable of film depolymerisation. Deep-sea plastispheres, hypersaline basins, and extraterrestrial analog sites further reveal archaeal colonisation and metabolic versatility. This review synthesises metagenomic, enzymatic, and community-level evidence, critically evaluates archaeal advantages relative to bacteria and fungi, addresses persistent gaps, including limited polyolefin mineralisation and cultivation bias, and outlines priorities for enzyme engineering and consortia design. The work advances sustainable bioremediation strategies aligned with climate-action goals and circular-economy frameworks in extreme and space environments.
Expansion of the genetic alphabet with unnatural base pairs (UBPs) enables new approaches in protein engineering, synthetic biology, and biocontainment. Such applications rely on faithful incorporation and retention of UBPs in semi-synthetic systems, making their detection and monitoring essential tools for xenobiology. Current methods for detecting UBPs in DNA frequently rely on labelling strategies, specialised reagents, or advanced analytical instrumentation. These approaches increase cost, technical complexity, and turnaround time, limiting accessibility and scalability of xenobiological experiments. Here, we establish high-resolution melting (HRM) analysis as a rapid and accessible method for detecting the UBP NaM-TPT3 based on differences in melting temperature of short amplicons. The approach can be directly appended to standard PCR workflows using commonly available qPCR instrumentation, enabling fast and cost-effective screening of UBP incorporation and stability in DNA. After optimisation of HRM-specific PCR conditions for efficient UBP incorporation, we demonstrate that HRM analysis produces clear and reproducible melting signatures that distinguish natural and unnatural sequences and detect defined variant mixtures. The method is validated using non-amplified DNA controls and LC-MS analysis. By enabling low-cost, workflow-integrated verification of UBP presence using standard laboratory infrastructures, HRM provides a practical screening tool that lowers barriers to experimentation and accelerated iterative development of expanded genetic systems.
Lactobacillus crispatus is widely associated with optimal sexual and reproductive health outcomes. While L. crispatus genomes commonly harbor prophages, little is known about their genomic diversity and potential inducibility by clinically relevant compounds. We induced and characterized four bacteriophages from four L. crispatus strains isolated from vaginal secretions of South African adolescents. Sequenced viral DNA from induced phages was assembled, and their respective genomes were annotated and compared to bacteriophage reference genomes. All the phage genomes range in size from 42.9 to 48.3 kbp. Of the four phages, UC101 and UC164 shared <90% pairwise intergenomic similarity to reference phages, suggesting that they represent new species. To explore factors potentially associated with prophage activation, L. crispatus strains were exposed to physiological concentrations of copper ions and tenofovir, selected based on their common use by women in Africa and reported associations with altered vaginal bacterial community composition. The presence of phage-like particles following exposure to copper ions (2.0 × 10-6 M-3.0 × 10-6 M) and tenofovir (500 ng/mL) was observed by transmission electron microscopy, suggesting possible prophage activation under these conditions. This study provides new insights into the genomic diversity of inducible L. crispatus phages and presents hypothesis-generating evidence regarding their potential inducibility using copper ions and tenofovir.
Point-of-care ultrasound (POCUS) provides real-time diagnostic capabilities at the bedside. Implementing a POCUS program in an institution is a highly complex process. Coordinating the imaging workflow of numerous clinical specialties requires meticulous planning and appropriate oversight. This white paper describes the best practices for the critical pre-deployment phase of program implementation, after having established POCUS program governance. Important considerations during the pre-deployment phase include goal setting, scaling POCUS workflow across clinical, educational, and technological domains, and addressing budgetary concerns and complexity of deployment strategies. This paper also discusses the role of the POCUS workflow manager software in encounter-based imaging workflow and the role of a system-wide clinical ultrasound director. Furthermore, it outlines the necessary approvals needed to ensure compliance and program success, including securing approvals from key departments such as imaging informatics, information technology, cybersecurity, supply chain operations, clinical engineering, infection prevention, legal, and billing departments. Finally, it presents a sample comprehensive project charter to guide this complex integration process from business case development, to clinical go-live, emphasizing best practices for sustained adoption.
Poxviruses encode a plethora of proteins adapted to diverse cellular responses against viruses. The poxvirus-encoded E3-like proteins are multifunctional, regulating diverse cellular antiviral responses. The canonical Vaccinia E3-like proteins have two domains: an N-terminal Z-form nucleic acid-binding domain (Zα-BD) and a C-terminal double-stranded RNA-binding domain (dsRNA-BD). Using protein sequence and structural homology modeling, we identified dsRNA-BD-fold-containing proteins in all the poxviruses except avipoxviruses, salmon poxvirus, and entomopoxviruses. Furthermore, we show that the acquisition of these proteins likely happened under three distinct events and can be classified into three categories: (i) the E3-like proteins with dsRNA-BD with the presence or absence of the N-terminal domain; (ii) unconventional/putative dsRNA-BD-fold-like proteins, present in macropoxvirus and molluscipoxvirus, and (iii) the dsRNA-BD-containing protein present in crocodile poxvirus. Members of leporipoxvirus, waddenpoxvirus, cetaceanpoxvirus, and selected members of orthopoxvirus contain E3-like proteins missing the N-terminal Zα-BD required for necroptosis inhibition. Using AlphaFold, we also show that the Zα-BD of chordopoxviruses, E3-like proteins, is structurally more variable than the dsRNA-binding domain. Compared to orthopoxviruses that inhibit necroptosis and contain an N-terminus Zα-BD, our results show that leporipoxviruses induce receptor-interacting protein kinase (RIPK) RIPK1- and RIPK3-mediated necroptosis in human and mouse necroptosis-competent cell lines. These data suggest that leporipoxviruses lack countermeasures against necroptosis, unlike orthopoxviruses, which encode multiple key regulators of necroptosis, possibly due to a lack of selective pressure in their lagomorph host species.IMPORTANCEThe evolutionary arms race between viruses and their hosts has led to the viral acquisition of genes that antagonize the host's antiviral defenses. However, related viral and host proteins have evolved under positive, purifying, and neutral selection. Poxvirus-encoded E3-like proteins play a pivotal role in regulating the host's cellular antiviral and apoptotic responses. The two domains of canonical E3-like proteins, an N-terminal Z-form nucleic acid-binding domain (Zα-BD) and a C-terminal double-stranded RNA-binding domain (dsRNA-BD), have evolved under varying host immune selection pressures. Here, we demonstrate that the dsRNA-BD is structurally conserved among E3 orthologs, whereas the Zα-BD, involved in regulating necroptosis, exhibits structural diversity and is absent in some poxviruses. Leporipoxviruses, which lack Zα-BD-containing proteins and evolved in species without functional necroptosis, do activate necroptosis in necroptotic-competent cells. Our study thus highlights that a lack of selective pressure from the host can shape viral countermeasures and viral divergence.
Sickness, or sickness behavior, is a state of altered physiology and behavior generated by the brain-immune axis during infection, which is generally assumed to contribute to host defense. Here, we examine this assumption by framing sickness as organismal-scale immunity and explore predicted parallels with immunity at the cellular and tissue scales.
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Sauce-flavor Baijiu owes its layered aroma to a diverse microbial consortium fermenting under extreme, open, solid-state conditions. High-throughput sequencing has revealed marked spatiotemporal heterogeneity in community composition, yet a fundamental composition-function disconnect persists: bulk omics average signals across heterogeneous micro-niches and cultivation recovers only a minor fraction of total diversity, leaving "who is doing what" unresolved. Closing this disconnect is a prerequisite for rational design of fermentation microbiomes and demands cell-resolved functional tools within an iterative engineering framework. This review proposes that Single-Cell Raman Spectroscopy (SCRS) and its derivatives, including D2O-Raman activity mapping, scRACS-Seq phenotype-to-genome linkage, scRACS-Culture recovery of rare functional strains, and Intra-Ramanome Correlation Analysis (IRCA) predictive metabolic phenotyping, collectively provide a label-free, culture-independent toolkit suited to this role in solid-state matrices. We delineate how these single-cell insights feed each stage of a Design-Build-Test-Learn (DBTL) cycle, from phenotype-informed strain selection through consortium assembly and functional validation to data-driven iterative optimization. This convergence of cell-resolved functional dissection, synthetic ecology, and process analytical technologies establishes the foundation for advancing Sauce-flavor Baijiu from experience-dependent craftsmanship toward intelligent brewing.
Many studies have confirmed that a subset of children with autism spectrum disorder (ASD) have unusually high urinary concentrations of microbially-derived metabolites (MDMs) such as p-cresol sulfate and indoxyl sulfate. We hypothesized that these MDMs may affect neurodevelopment through the gut-brain axis and that a sub-phenotype characterized by gut dysbiosis may be present in most ASD individuals. This multi-site study involved measuring the concentrations of many MDMs in the urine of 52 children with ASD and 47 healthy, typically developing (TD) children, aged 2 to 11 years. The measurements were conducted first with semiquantitative Liquid Chromatography and Mass Spectrometry (LC-MS), followed by targeted quantitative LC-MS. The ASD group had significantly higher concentrations of many MDMs compared to the TD group. The MDMs included phenylalanine-derived, tryptophan-derived, and yeast-derived MDMs. Almost all children with ASD had one or more MDMs at concentrations above any TD child, and sometimes 100-1000× higher. The children with ASD had an average of 3 MDMs at levels above any TD child, compared to zero (by definition) for the TD children. Classification using one or more elevated MDM yielded a sensitivity of 90% and a specificity of 100%. This MDM SystemTM is a promising non-invasive method for diagnostic screening for ASD in children ages 2 to 11 years. These data also suggest approximately 90% of children with ASD have a distinct phenotype of ASD, which we propose naming ASD associated with Microbially-Derived Metabolites (ASD-MDM), defined by objective, quantitative laboratory measurements of these metabolites in urine.
Tau is an intrinsically disordered microtubule-associated protein that performs diverse roles in neuronal physiology, including regulation of microtubule stability, intracellular transport, and synaptic signaling. These functions are dynamically regulated by an extensive array of post-translational modifications (PTMs) that collectively shape tau conformation, interactions, localization, and turnover. Under physiological conditions, PTMs act as a regulatory system that enables tau to transition between functional states in response to cellular cues. In neurodegenerative diseases collectively known as tauopathies, however, this finely balanced modification landscape becomes disrupted, leading to tau mislocalization, impaired clearance, and assembly into toxic oligomers and fibrillar aggregates. Although phosphorylation has historically dominated the tau field, growing evidence indicates that multiple PTMs, including acetylation, ubiquitination, truncation, oxidation, nitration, methylation, and glycosylation, cooperatively influence tau structure and pathogenic potential. Recent proteomic studies reveal that tau can harbor dozens of modifications simultaneously, highlighting the importance of understanding PTMs as an integrated regulatory network rather than independent events. Crosstalk between modifications can generate synergistic or antagonistic effects that influence tau aggregation, proteostasis, and propagation. In this review, we synthesize current knowledge of major tau PTMs and highlight emerging principles governing their interactions. We discuss how dysregulation of PTM networks contributes to tau state transitions during aging and neurodegeneration and consider how targeting PTM-regulating enzymes may provide therapeutic strategies for Alzheimer's disease and related tauopathies.