Uncertainty Quantification of Linear Scaling, Machine Learning, and Density Functional Theory Derived Thermodynamics for the Catalytic Partial Oxidation of Methane on Rhodium.

Accurate and complete microkinetic models (MKMs) are powerful for anticipating the behavior of complex chemical systems at different operating conditions. In heterogeneous catalysis, they can be further used for the rapid development and screening of new catalysts. Density functional theory (DFT) is often used to calculate the parameters used in MKMs with relatively high fidelity. However, given the high cost of DFT calculations for adsorbates in heterogeneous catalysis, linear scaling relations (LSRs) and machine learning (ML) models were developed to give rapid estimates of the parameters in MKM. Regardless of the method, few studies have attempted to quantify the uncertainty in catalytic MKMs, as the uncertainties are often orders of magnitude larger than those for gas phase models. This study explores uncertainty quantification and Bayesian Parameter Estimation for thermodynamic parameters calculated by DFT, LSRs, and GemNet-OC, a ML model developed under the Open Catalyst Project. A model for catalytic partial oxidation of methane (CPOX) on Rhodium was chosen as a case study, in which the model's thermodynamic parameters and their associated uncertainties were determined using DFT, LSR, and GemNet-OC. Markov Chain Monte Carlo coupled with Ensemble Slice Sampling was used to sample the highest probability density (HPD) region of the posterior and determine the maximum of the a posteriori (MAP) for each thermodynamic parameter included. The optimized microkinetic models for each of the three estimation methods had quite similar mechanisms and agreed well with the experimental data for gas phase mole fractions. Exploration of the HPD region of the posterior further revealed that adsorbed hydroxide and oxygen likely bind on facets other than Rhodium 111. The demonstrated workflow addresses the issue of inaccuracies arising from the integration of data from multiple sources by considering both experimental and computational uncertainties, and further reveals information about the active site that would not have been discovered without considering the posterior.

ICON 2023: International Scientific Tendinopathy Symposium Consensus - the core outcome set for Achilles tendinopathy (COS-AT) using a systematic review and a Delphi study of professional participants and patients.

To develop a core outcome set for Achilles tendinopathy (COS-AT) for use in clinical trials we performed a five-step process including (1) a systematic review of available outcome measurement instruments, (2) an online survey on truth and feasibility of the available measurement instruments, (3) an assessment of the methodological quality of the selected outcome measurement instruments, (4) an online survey on the outcome measurement instruments as COS and (5) a consensus in-person meeting. Both surveys were completed by healthcare professionals and patients. The Outcome Measures in Rheumatology guidelines with a 70% threshold for consensus were followed. We identified 233 different outcome measurement instruments from 307 included studies; 177 were mapped within the International Scientific Tendinopathy Symposium Consensus core domains. 31 participants (12 patients) completed the first online survey (response rate 94%). 22/177 (12%) outcome measurement instruments were deemed truthful and feasible and their measurement properties were evaluated. 29 participants (12 patients) completed the second online survey (response rate 88%) and three outcome measurement instruments were endorsed: the Victorian Institute of Sports Assessment-Achilles questionnaire, the single-leg heel rise test and evaluating pain after activity using a Visual Analogue Scale (VAS, 0-10). 12 participants (1 patient) attended the final consensus meeting, and 1 additional outcome measurement instrument was endorsed: evaluating pain during activity/loading using a VAS (0-10). It is recommended that the identified COS-AT will be used in future clinical trials evaluating the effectiveness of an intervention. This will facilitate comparing outcomes of intervention strategies, data pooling and further progression of knowledge about AT. As COS-AT is implemented, further evidence on measurement properties of included measures and new outcome measurement instruments should lead to its review and refinement.

Association Between Utilization of Services and Perioperative Outcomes for Lung Cancer Resection.

INTRODUCTION: Lung cancer resection has largely focused on perioperative outcomes (eg, mortality) to benchmark performance. While variations in perioperative outcomes and in utilization of services (eg, ambulatory procedures, hospitalization) have been independently demonstrated, there has been limited evaluation of associations between these outcomes. We evaluated the association between perioperative outcomes and utilization of services to evaluate provider performance across a broader context of care. PATIENTS AND METHODS: This was a retrospective cohort study of patients undergoing lung cancer resection in 2017 to 2019. We utilized hierarchical logistic regression models to determine risk- and reliability-adjusted mortality and risk-adjusted utilization of services, at the hospital-level. We then evaluated utilization of services across quartiles of perioperative mortality. RESULTS: A total of 15,168 patients across 297 hospitals underwent lung cancer resection. Mean risk- and reliability-adjusted 90-day mortality varied between 1.58% (95% CI, 1.54%-1.62%) and 2.74% (95% CI, 2.59%-2.90%) across quartiles. Risk-adjusted utilization of all ambulatory procedures was highest in the best performing (lowest mortality) quartile at 37.7% (95% CI, 33.6%-41.8%). Additionally, risk-adjusted inpatient utilization prior to and after surgery was lowest in the best performing quartile at 15% (95% CI, 13.7%-16.3%) and 19.3% (95% CI, 17.5%-21.0%), respectively. CONCLUSIONS: Hospitals with the lowest perioperative mortality demonstrated trends towards using more outpatient resources prior to surgery, but fewer inpatient services surrounding lung cancer resection. This correlation highlights the importance of incorporating utilization of services in addition to other metrics to profile the efficiency and effectiveness of centers performing lung cancer resection across a broader spectrum of care.

Implementing the Blowers-Masel Approximation to Scale Activation Energy Based on Reaction Enthalpy in Mean-Field Microkinetic Modeling for Catalytic Methane Partial Oxidation.

Mean-field microkinetic modeling is a powerful tool for catalyst design and the simulation of catalytic processes. The reaction enthalpies in a microkinetic model often need to be adjusted when changing species' binding energies to model different catalysts, when performing thermodynamic sensitivity analyses, and when fitting experimental data. When altering reaction enthalpies, the activation energies should also be reasonably altered to ensure realistic reaction rates. The Blowers-Masel approximation (BMA) relates the reaction barrier to the reaction enthalpy. Unlike the Brønsted-Evans-Polani relationship, the BMA requires less data because only one parameter, the intrinsic activation energy, needs to be determined. We validate this application of BMA relations to model surface reactions by comparing against density functional theory data taken from the literature. By incorporating the BMA rate description into the open-source Cantera software, we enable a new workflow, demonstrated herein, allowing rapid screening of catalysts using linear scaling relationships and BMA kinetics within the process simulation software. For demonstration purposes, a catalyst screening for catalytic methane partial oxidation on 81 hypothetical metals is conducted. We compared the results with and without BMA-corrected rates. The heat maps of various descriptors (e.g., CH4 conversion, syngas yield) show that using BMA rates instead of Arrhenius rates (with constant activation energies) changes which metals are most active. Heat maps of sensitivity analyses can help identify which reactions or species are the most influential in shaping the descriptor map patterns. Our findings indicate that while using BMA-adjusted rates did not markedly affect the most sensitive reactions, it did change the most influential species.

Mathematical model of intestinal lipolysis of a long-chain triglyceride.

Lipids are an important component of food and oral drug formulations. Upon release into gastrointestinal fluids, triglycerides, common components of foods and drug delivery systems, form emulsions and are digested into simpler amphiphilic lipids (e.g., fatty acids) that can associate with intestinal bile micelles and impact their drug solubilization capacity. Digestion of triglycerides is dynamic and dependent on lipid quantity and type, and quantities of other components in the intestinal environment (e.g., bile salts, lipases). The ability to predict lipid digestion kinetics in the intestine could enhance understanding of lipid impact on the fate of co-administered compounds (e.g., drugs, nutrients). In this study, we present a kinetic model that can predict the lipolysis of emulsions of triolein, a model long-chain triglyceride, as a function of triglyceride amount, droplet size, and quantity of pancreatic lipase in an intestinal environment containing bile micelles. The model is based on a Ping Pong Bi Bi mechanism coupled with quantitative analysis of partitioning of lipolysis products in colloids, including bile micelles, in solution. The agreement of lipolysis model predictions with experimental data suggests that the mechanism and proposed assumptions adequately represent triglyceride digestion in a simulated intestinal environment. In addition, we demonstrate the value of such a model over simpler, semi-mechanistic models reported in the literature. This lipolysis framework can serve as a basis for modeling digestion kinetics of different classes of triglycerides and other complex lipids as relevant in food and drug delivery systems.

Peripancreatic fluid collections following distal pancreatectomy and splenectomy-when is intervention warranted?

BACKGROUND: Peripancreatic fluid collections after distal pancreatectomy and splenectomy are commonly identified on postoperative cross-sectional imaging. This study aimed to determine the incidence, natural history, and indications for intervention. METHODS: We conducted a retrospective review of patients with peripancreatic fluid collections after distal pancreatectomy with or without splenectomy between 2013 and 2018, approved by our institutional review board. The chi-square test was used for categorical variables, the Mann-Whitney U test for continuous variables, and Fisher's exact test was used for values in which the sample size was less than 5 to compare data. RESULTS: During the study period, 235 patients underwent distal pancreatectomy with or without splenectomy, and 182 patients with postoperative imaging were included. In the cohort of patients with postoperative imaging, 83 (46%) had peripancreatic fluid collections, of which 46 (55%) were symptomatic fluid collections (SFCs) and 37 (45%) were asymptomatic fluid collections (AFCs). Those with SFC had a higher incidence of postoperative morbidity (46% vs 8%; P = .0002), most commonly postoperative pancreatic fistula (90%). Of patients with SFC, 34 (74%) underwent treatment via percutaneous drainage (n = 26), endoscopic drainage (n = 7), or antibiotics alone (n = 1). AFCs (n = 37) were observed. Collections that were intervened upon resolved significantly faster than those observed, 3.5 months vs 13.2 months (P < .0001), respectively. CONCLUSION: Asymptomatic patients may be observed with or without serial imaging and the AFC will typically resolve spontaneously with time. Patients who develop symptoms should generally be intervened upon with drainage if deemed feasible, given that this reduces the time to resolution.

XBB.1.5 monovalent booster improves antibody binding and neutralization against emerging SARS-CoV-2 Omicron variants.

The rapid emergence of divergent SARS-CoV-2 variants has led to an update of the COVID-19 booster vaccine to a monovalent version containing the XBB.1.5 spike. To determine the neutralization breadth following booster immunization, we collected blood samples from 24 individuals pre- and post-XBB.1.5 mRNA booster vaccination (∼1 month). The XBB.1.5 booster improved both neutralizing activity against the ancestral SARS-CoV-2 strain (WA1) and the circulating Omicron variants, including EG.5.1, HK.3, HV.1, XBB.1.5 and JN.1. Relative to the pre-boost titers, the XBB.1.5 monovalent booster induced greater total IgG and IgG subclass binding, particular IgG4, to the XBB.1.5 spike as compared to the WA1 spike. We evaluated antigen-specific memory B cells (MBCs) using either spike or receptor binding domain (RBD) probes and found that the monovalent booster largely increases non-RBD cross-reactive MBCs. These data suggest that the XBB.1.5 monovalent booster induces cross-reactive antibodies that neutralize XBB.1.5 and related Omicron variants.

Iterating toward change: Improving student-centered teaching through the STEM faculty institute (STEMFI).

One of the primary reasons why students leave STEM majors is due to the poor quality of instruction. Teaching practices can be improved through professional development programs; however, several barriers exist. Creating lasting change by overcoming these barriers is the primary objective of the STEM Faculty Institute (STEMFI). STEMFI was designed according to the framework established by Ajzen's Theory of Planned Behavior. To evaluate its effectiveness, the Classroom Observation Protocol for Undergraduate STEM (COPUS) tool was used before and after an intensive year-long faculty development program and analyzed using copusprofiles.org, a tool that classifies each COPUS report into one of three instructional styles: didactic, interactive lecture, and student-centered. We report the success of our program in changing faculty teaching behaviors and we categorize them into types of reformers. Then, thematically coded post-participation interviews give us clues into the characteristics of each type of reformer. Our results demonstrate that faculty can significantly improve the student-centeredness of their teaching practices in a relatively short time. We also discuss the implications of faculty attitudes for future professional development efforts.

TENDINopathy Severity Assessment - Achilles (TENDINS-A): Development and Content Validity Assessment of a New Patient-Reported Outcome Measure for Achilles Tendinopathy.

OBJECTIVE: To develop a new patient-reported outcome measure (PROM) assessing TENDINopathy Severity of the Achilles (TENDINS-Achilles) and evaluate its content validity. DESIGN: Mixed-methods, modified Delphi. METHODS: We performed 1 round of semistructured one-on-one interview responses with professionals and patients, for initial item generation. This was followed by 1 round of survey responses for professionals and a final round of semistructured one-on-one interviews with patients. The work culminated in a PROM to quantify Achilles tendinopathy severity under the core health domain of disability. Participants identified 3 subdomains contributing to the severity of disability of Achilles tendinopathy: pain, symptoms, and functional capacity. RESULTS: All 8 patient participants invited to participate were enrolled. Forty professional participants (50% women, six different continents) were invited to participate and 30 were enrolled (75% response rate). Therefore, a total of 30 professionals and 8 patients were included within this study. Following 3 rounds of qualitative or quantitative feedback, this study has established the content validity of TENDINS-A (good relevance, comprehensibility, and comprehensiveness) as a new PROM to assess the severity of Achilles tendinopathy, which assesses aspects of pain, symptoms, and functional capacity. CONCLUSION: TENDINS-A has established content validity and is appropriate for use with clinical and research populations. We recommend users interpret TENDINS-A results cautiously, until further testing evaluates the most appropriate scoring scale, reliability, construct validity, criterion validity, and responsiveness of TENDINS-A. Until these psychometric properties are established, we suggest using TENDINS-A alongside existing tools. J Orthop Sports Phys Ther 2023;53(11):1-16. Epub: 24 August 2023. doi:10.2519/jospt.2023.11964.

Factors that influence STEM faculty use of evidence-based instructional practices: An ecological model.

Traditional teaching practices in undergraduate science, technology, engineering, and mathematics (STEM) courses have failed to support student success, causing many students to leave STEM fields and disproportionately affecting women and students of color. Although much is known about effective STEM teaching practices, many faculty continue to adhere to traditional methods, such as lecture. In this study, we investigated the factors that affect STEM faculty members' instructional decisions about evidence-based instructional practices (EBIPs). We performed a qualitative analysis of semi-structured interviews with faculty members from the Colleges of Physical and Mathematical Sciences, Life Sciences, and Engineering who took part in a professional development program to support the use of EBIPs by STEM faculty at the university. We used an ecological model to guide our investigation and frame the results. Faculty identified a variety of personal, social, and contextual factors that influenced their instructional decision-making. Personal factors included attitudes, beliefs, and self-efficacy. Social factors included the influence of students, colleagues, and administration. Contextual factors included resources, time, and student characteristics. These factors interact with each other in meaningful ways that highlight the hyper-local social contexts that exist within departments and sub-department cultures, the importance of positive feedback from students and colleagues when implementing EBIPs, and the need for support from the administration for faculty who are in the process of changing their teaching.

Endometrial hyperplasia with loss of APC in a novel population of Lyz2-expressing mouse endometrial epithelial cells.

Loss of heterozygosity and promoter hypermethylation of APC is frequently observed in human endometrial cancer, which is the most common gynecological cancer in the USA, but its carcinogenic driver status in the endometrial epithelium has not been confirmed. We have identified a novel population of progenitor endometrial epithelial cells (EECs) in mice that express lysozyme M (LysM) and give rise to approximately 15% of all EECs in adult mice. LysM is a glycoside hydrolase that is encoded by Lyz2 and functions to protect cells from bacteria as part of the innate immune system. Its expression has been shown in a subset of hematopoietic stem cells and in specialized lung and small intestinal epithelial cells. Conditional deletion of Apc in LysM + EECs results in significantly more epithelial cells compared to wild-type mice. At 5 months of age, the ApccKO mice have enlarged uterine horns with pathology that is consistent with endometrial hyperplasia with cystic endometrial glands, non-villous luminal papillae and nuclear atypia. Nuclear accumulation of ß-catenin and ERα, both of which are known to induce endometrial hyperplasia, was observed in the EECs of the ApccKO mice. These results confirm that loss of APC in EECs can result in a phenotype similar to endometrial hyperplasia.

RMG Database for Chemical Property Prediction.

The Reaction Mechanism Generator (RMG) database for chemical property prediction is presented. The RMG database consists of curated datasets and estimators for accurately predicting the parameters necessary for constructing a wide variety of chemical kinetic mechanisms. These datasets and estimators are mostly published and enable prediction of thermodynamics, kinetics, solvation effects, and transport properties. For thermochemistry prediction, the RMG database contains 45 libraries of thermochemical parameters with a combination of 4564 entries and a group additivity scheme with 9 types of corrections including radical, polycyclic, and surface absorption corrections with 1580 total curated groups and parameters for a graph convolutional neural network trained using transfer learning from a set of >130 000 DFT calculations to 10 000 high-quality values. Correction schemes for solvent-solute effects, important for thermochemistry in the liquid phase, are available. They include tabulated values for 195 pure solvents and 152 common solutes and a group additivity scheme for predicting the properties of arbitrary solutes. For kinetics estimation, the database contains 92 libraries of kinetic parameters containing a combined 21 000 reactions and contains rate rule schemes for 87 reaction classes trained on 8655 curated training reactions. Additional libraries and estimators are available for transport properties. All of this information is easily accessible through the graphical user interface at https://rmg.mit.edu. Bulk or on-the-fly use can be facilitated by interfacing directly with the RMG Python package which can be installed from Anaconda. The RMG database provides kineticists with easy access to estimates of the many parameters they need to model and analyze kinetic systems. This helps to speed up and facilitate kinetic analysis by enabling easy hypothesis testing on pathways, by providing parameters for model construction, and by providing checks on kinetic parameters from other sources.

Isolation and Identification of Vascular Endothelial Cells from Distinct Adipose Depots for Downstream Applications.

Vascular endothelial cells lining the wall of the vascular system play important roles in a variety of physiological processes, including vascular tone regulation, barrier functions, and angiogenesis. Endothelial cell dysfunction is a hallmark predictor and major driver for the progression of severe cardiovascular diseases, yet the underlying mechanisms remain poorly understood. The ability to isolate and perform analyses on endothelial cells from various vascular beds in their native form will give insight into the processes of cardiovascular disease. This protocol presents the procedure for the dissection of mouse subcutaneous and mesenteric adipose tissues, followed by isolation of their respective arterial vasculature. The isolated arteries are then digested using a specific cocktail of digestive enzymes focused on liberating functionally viable endothelial cells. The digested tissue is assessed by flow cytometry analysis using CD31+/CD45- cells as markers for positive endothelial cell identification. Cells can be sorted for immediate downstream functional assays or used to generate primary cell lines. The technique of isolating and digesting arteries from different vascular beds will provide options for researchers to evaluate freshly isolated vascular cells from arteries of interest and allow them to perform a wide range of functional tests on specific cell types.

Erythroid differentiation in mouse erythroleukemia cells depends on Tmod3-mediated regulation of actin filament assembly into the erythroblast membrane skeleton.

Erythroid differentiation (ED) is a complex cellular process entailing morphologically distinct maturation stages of erythroblasts during terminal differentiation. Studies of actin filament (F-actin) assembly and organization during terminal ED have revealed essential roles for the F-actin pointed-end capping proteins, tropomodulins (Tmod1 and Tmod3). Tmods bind tropomyosins (Tpms), which enhance Tmod capping and F-actin stabilization. Tmods can also nucleate F-actin assembly, independent of Tpms. Tmod1 is present in the red blood cell (RBC) membrane skeleton, and deletion of Tmod1 in mice leads to a mild compensated anemia due to mis-regulated F-actin lengths and membrane instability. Tmod3 is not present in RBCs, and global deletion of Tmod3 leads to embryonic lethality in mice with impaired ED. To further decipher Tmod3's function during ED, we generated a Tmod3 knockout in a mouse erythroleukemia cell line (Mel ds19). Tmod3 knockout cells appeared normal prior to ED, but showed defects during progression of ED, characterized by a marked failure to reduce cell and nuclear size, reduced viability, and increased apoptosis. Tmod3 does not assemble with Tmod1 and Tpms into the Triton X-100 insoluble membrane skeleton during ED, and loss of Tmod3 had no effect on α1,ß1-spectrin and protein 4.1R assembly into the membrane skeleton. However, F-actin, Tmod1 and Tpms failed to assemble into the membrane skeleton during ED in absence of Tmod3. We propose that Tmod3 nucleation of F-actin assembly promotes incorporation of Tmod1 and Tpms into membrane skeleton F-actin, and that this is integral to morphological maturation and cell survival during erythroid terminal differentiation.

ICON 2020-International Scientific Tendinopathy Symposium Consensus: A Systematic Review of Outcome Measures Reported in Clinical Trials of Achilles Tendinopathy.

BACKGROUND: Nine core domains for tendinopathy have been identified. For Achilles tendinopathy there is large variation in outcome measures used, and how these fit into the core domains has not been investigated. OBJECTIVE: To identify all available outcome measures outcome measures used to assess the clinical phenotype of Achilles tendinopathy in prospective studies and to map the outcomes measures into predefined health-related core domains. DESIGN: Systematic review. DATA SOURCES: Embase, MEDLINE (Ovid), Web of Science, CINAHL, The Cochrane Library, SPORTDiscus and Google Scholar. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Clinical diagnosis of Achilles tendinopathy, sample size ≥ ten participants, age ≥ 16 years, and the study design was a randomized or non-randomized clinical trial, observational cohort, single-arm intervention, or case series. RESULTS: 9376 studies were initially screened and 307 studies were finally included, totaling 13,248 participants. There were 233 (177 core domain) different outcome measures identified across all domains. For each core domain outcome measures were identified, with a range between 8 and 35 unique outcome measures utilized for each domain. The proportion of studies that included outcomes for predefined core domains ranged from 4% for the psychological factors domain to 72% for the disability domain. CONCLUSION: 233 unique outcome measures for Achilles tendinopathy were identified. Most frequently, outcome measures were used within the disability domain. Outcome measures assessing psychological factors were scarcely used. The next step in developing a core outcome set for Achilles tendinopathy is to engage patients, clinicians and researchers to reach consensus on key outcomes measures. PROSPERO REGISTRATION: CRD42020156763.

Quantifying the Impact of Parametric Uncertainty on Automatic Mechanism Generation for CO2 Hydrogenation on Ni(111).

Automatic mechanism generation is used to determine mechanisms for the CO2 hydrogenation on Ni(111) in a two-stage process while considering the correlated uncertainty in DFT-based energetic parameters systematically. In a coarse stage, all the possible chemistry is explored with gas-phase products down to the ppb level, while a refined stage discovers the core methanation submechanism. Five thousand unique mechanisms were generated, which contain minor perturbations in all parameters. Global uncertainty assessment, global sensitivity analysis, and degree of rate control analysis are performed to study the effect of this parametric uncertainty on the microkinetic model predictions. Comparison of the model predictions with experimental data on a Ni/SiO2 catalyst find a feasible set of microkinetic mechanisms within the correlated uncertainty space that are in quantitative agreement with the measured data, without relying on explicit parameter optimization. Global uncertainty and sensitivity analyses provide tools to determine the pathways and key factors that control the methanation activity within the parameter space. Together, these methods reveal that the degree of rate control approach can be misleading if parametric uncertainty is not considered. The procedure of considering uncertainties in the automated mechanism generation is not unique to CO2 methanation and can be easily extended to other challenging heterogeneously catalyzed reactions.

The ubiquitous mitochondrial protein unfoldase CLPX regulates erythroid heme synthesis by control of iron utilization and heme synthesis enzyme activation and turnover.

Heme plays a critical role in catalyzing life-essential redox reactions in all cells, and its synthesis must be tightly balanced with cellular requirements. Heme synthesis in eukaryotes is tightly regulated by the mitochondrial AAA+ unfoldase CLPX (caseinolytic mitochondrial matrix peptidase chaperone subunit X), which promotes heme synthesis by activation of δ-aminolevulinate synthase (ALAS/Hem1) in yeast and regulates turnover of ALAS1 in human cells. However, the specific mechanisms by which CLPX regulates heme synthesis are unclear. In this study, we interrogated the mechanisms by which CLPX regulates heme synthesis in erythroid cells. Quantitation of enzyme activity and protein degradation showed that ALAS2 stability and activity were both increased in the absence of CLPX, suggesting that CLPX primarily regulates ALAS2 by control of its turnover, rather than its activation. However, we also showed that CLPX is required for PPOX (protoporphyrinogen IX oxidase) activity and maintenance of FECH (ferrochelatase) levels, which are the terminal enzymes in heme synthesis, likely accounting for the heme deficiency and porphyrin accumulation observed in Clpx-/- cells. Lastly, CLPX is required for iron utilization for hemoglobin synthesis during erythroid differentiation. Collectively, our data show that the role of CLPX in yeast ALAS/Hem1 activation is not conserved in vertebrates as vertebrates rely on CLPX to regulate ALAS turnover as well as PPOX and FECH activity. Our studies reveal that CLPX mutations may cause anemia and porphyria via dysregulation of ALAS, FECH, and PPOX activities, as well as of iron metabolism.