Manipulation of Photosensory and Circadian Signalling Restricts Phenotypic Plasticity in Response to Changing Environmental Conditions in Arabidopsis.

Plants exploit phenotypic plasticity to adapt their growth and development to prevailing environmental conditions. Interpretation of light and temperature signals are aided by the circadian system which provides a temporal context. Phenotypic plasticity provides a selective and competitive advantage in nature but is obstructive during large-scale, intensive agricultural practices since economically important traits (including vegetative growth and flowering time) can widely vary depending on local environmental conditions. This prevents accurate prediction of harvesting times and produces a variable crop. We sought to restrict phenotypic plasticity and circadian regulation by manipulating signalling systems that govern plants' responses to environmental signals. Mathematical modelling of plant growth and development predicted reduced plant responses to changing environments when circadian and light signaling pathways were manipulated. We tested this hypothesis by utilising a constitutively-active allele of the plant photoreceptor phytochromeB, along with disruption of the circadian system via mutation of EARLY FLOWERING3. We found that these manipulations produced plants that were less responsive to light and temperature cues and which failed to anticipate dawn. These engineered plants have uniform vegetative growth and flowering time, demonstrating how phenotypic plasticity can be limited whilst maintaining plant productivity. This has significant implications for future agriculture in both open fields and controlled environments.

Three enzymes governed the rise of O2 on Earth.

Current views of O2 accumulation in Earth history depict three phases: The onset of O2 production by ∼2.4 billion years ago; 2 billion years of stasis at ∼1 % of modern atmospheric levels; and a rising phase, starting about 500 million years ago, in which oxygen eventually reached modern values. Purely geochemical mechanisms have been proposed to account for this tripartite time course of Earth oxygenation. In particular the second phase, the long period of stasis between the advent of O2 and the late rise to modern levels, has posed a puzzle. Proposed solutions involve Earth processes (geochemical, ecosystem, day length). Here we suggest that Earth oxygenation was not determined by geochemical processes. Rather it resulted from emergent biological innovations associated with photosynthesis and the activity of only three enzymes: 1) The oxygen evolving complex of cyanobacteria that makes O2; 2) Nitrogenase, with its inhibition by O2 causing two billion years of oxygen level stasis; 3) Cellulose synthase of land plants, which caused mass deposition and burial of carbon, thus removing an oxygen sink and therefore increasing atmospheric O2. These three enzymes are endogenously produced by, and contained within, cells that have the capacity for exponential growth. The catalytic properties of these three enzymes paved the path of Earth's atmospheric oxygenation, requiring no help from Earth other than the provision of water, CO2, salts, colonizable habitats, and sunlight.

Effect of Insecticide Exposure Across Multiple Generations of the Earthworm Eisenia andrei.

The toxicity of neonicotinoids and many of their replacement insecticides to nontarget soil invertebrates such as earthworms has previously been established. However, the long-term effects of these substances on these organisms are largely unknown. In the field of soil ecotoxicology, lumbricid earthworms such as Eisenia andrei are used extensively due to the availability of standardized test methods and their adaptability to laboratory culture and testing. Multigenerational studies have gained popularity and attention in recent years, with a shift toward the use of long-term assays and lower concentrations of test chemicals. The use of exposure concentrations that include those measured in a monitoring program carried out by the Government of Ontario presents a realistic exposure scenario that may not show significant effects in contemporary, shorter term studies. We used current standardized test methods as a basis for the development of multigenerational studies on E. andrei. The effects of exposure to a single application of the insecticides thiamethoxam and cyantraniliprole on the survival and reproduction of E. andrei were observed over three (thiamethoxam) or two (cyantraniliprole) generations using consecutive reproduction tests. No significant impacts on adult survival were reported in any generation for either insecticide, whereas reproduction decreased between the first and second generations in the thiamethoxam test, with median effective concentration (EC50) values of 0.022 mg/kg dry weight reported for the first generation compared with 0.002 mg/kg dry weight in the second generation. For cyantraniliprole, an EC50 of 0.064 was determined for the first generation compared with 0.016 mg/kg dry weight in the second generation. A third generation was completed for the thiamethoxam test, and a significant decrease in reproduction was observed in all treatments and controls compared with previous generations. No significant difference between thiamethoxam treatments and the control treatment was reported for the third generation. Collectively, these data indicate that exposure of oligochaetes to these two insecticides at concentrations representative of field conditions may result in long-term stresses. Environ Toxicol Chem 2024;00:1-13. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Evaluation of multiple-vendor AI autocontouring solutions.

BACKGROUND: Multiple artificial intelligence (AI)-based autocontouring solutions have become available, each promising high accuracy and time savings compared with manual contouring. Before implementing AI-driven autocontouring into clinical practice, three commercially available CT-based solutions were evaluated. MATERIALS AND METHODS: The following solutions were evaluated in this work: MIM-ProtégéAI+ (MIM), Radformation-AutoContour (RAD), and Siemens-DirectORGANS (SIE). Sixteen organs were identified that could be contoured by all solutions. For each organ, ten patients that had manually generated contours approved by the treating physician (AP) were identified, totaling forty-seven different patients. CT scans in the supine position were acquired using a Siemens-SOMATOMgo 64-slice helical scanner and used to generate autocontours. Physician scoring of contour accuracy was performed by at least three physicians using a five-point Likert scale. Dice similarity coefficient (DSC), Hausdorff distance (HD) and mean distance to agreement (MDA) were calculated comparing AI contours to "ground truth" AP contours. RESULTS: The average physician score ranged from 1.00, indicating that all physicians reviewed the contour as clinically acceptable with no modifications necessary, to 3.70, indicating changes are required and that the time taken to modify the structures would likely take as long or longer than manually generating the contour. When averaged across all sixteen structures, the AP contours had a physician score of 2.02, MIM 2.07, RAD 1.96 and SIE 1.99. DSC ranged from 0.37 to 0.98, with 41/48 (85.4%) contours having an average DSC ≥ 0.7. Average HD ranged from 2.9 to 43.3 mm. Average MDA ranged from 0.6 to 26.1 mm. CONCLUSIONS: The results of our comparison demonstrate that each vendor's AI contouring solution exhibited capabilities similar to those of manual contouring. There were a small number of cases where unusual anatomy led to poor scores with one or more of the solutions. The consistency and comparable performance of all three vendors' solutions suggest that radiation oncology centers can confidently choose any of the evaluated solutions based on individual preferences, resource availability, and compatibility with their existing clinical workflows. Although AI-based contouring may result in high-quality contours for the majority of patients, a minority of patients require manual contouring and more in-depth physician review.

Characterization of Springtail (Arrhopalites caecus) for Use in Soil Ecotoxicity Testing.

Springtails (subclass: Collembola) represent one of the most extensively studied invertebrate groups in soil ecotoxicology. This is because of their ease of laboratory culture, significant ecological role, and sensitivity to environmental contaminants. Folsomia candida (family: Isotomidae) is a globally widespread parthenogenetic species that is prevalent in laboratory toxicity testing with springtails. Conversely, Arrhopalites caecus (family: Arrhopalitidae), a parthenogenic globular springtail species, remains untested in soil ecotoxicology. This species is found in diverse habitats, including cave systems and forest leaf litter, and has a global distribution. The sensitivity of A. caecus to environmental contaminants, such as neonicotinoid insecticides, as well as its life history and optimal culturing conditions, are largely unknown. The present study describes the establishment of a pure A. caecus laboratory culture and characterization of its life cycle and culturing conditions. We assessed the sensitivity of A. caecus to various insecticides, including exposures to the neonicotinoid thiamethoxam in soil and through a novel feeding assay as well as to clothianidin and cyantraniliprole in spiked soil exposures. In 7- and 14-day exposures to thiamethoxam in agricultural soil, the 50% lethal concentration (LC50) values were determined to be 0.129 mg/kg dry weight and 0.010 mg/kg dry weight, respectively. The 14-day LC50 for exposure to thiamethoxam via spiked food was determined to be 0.307 mg/kg dry weight. In addition, the 28-day 50% effect concentration for inhibition of juvenile production from cyantraniliprole exposure in the same soil type was 0.055 mg/kg dry weight. Challenges encountered in using this species included susceptibility to mite infestation and low adult survival rates in the 28-day cyantraniliprole test. Environ Toxicol Chem 2024;00:1-16. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Synthesis and biological evaluation of orally active anti-Trypanosoma agents.

In previous studies, we developed anti-trypanosome tubulin inhibitors with promising in vitro selectivity and activity against Human African Trypanosomiasis (HAT). However, for such agents, oral activity is crucial. This study focused on further optimizing these compounds to enhance their ligand efficiency, aiming to reduce bulkiness and hydrophobicity, which should improve solubility and, consequently, oral bioavailability. Using Trypanosoma brucei brucei cells as the parasite model and human normal kidney cells and mouse macrophage cells as the host model, we evaluated 30 new analogs synthesized through combinatorial chemistry. These analogs have fewer aromatic moieties and lower molecular weights than their predecessors. Several new analogs demonstrated IC50s in the low micromolar range, effectively inhibiting trypanosome cell growth without harming mammalian cells at the same concentration. We conducted a detailed structure-activity relationship (SAR) analysis and a docking study to assess the compounds' binding affinity to trypanosome tubulin homolog. The results revealed a correlation between binding energy and anti-Trypanosoma activity. Importantly, compound 7 displayed significant oral activity, effectively inhibiting trypanosome cell proliferation in mice.

The radical impact of oxygen on prokaryotic evolution-enzyme inhibition first, uninhibited essential biosyntheses second, aerobic respiration third.

Molecular oxygen is a stable diradical. All O2-dependent enzymes employ a radical mechanism. Generated by cyanobacteria, O2 started accumulating on Earth 2.4 billion years ago. Its evolutionary impact is traditionally sought in respiration and energy yield. We mapped 365 O2-dependent enzymatic reactions of prokaryotes to phylogenies for the corresponding 792 protein families. The main physiological adaptations imparted by O2-dependent enzymes were not energy conservation, but novel organic substrate oxidations and O2-dependent, hence O2-tolerant, alternative pathways for O2-inhibited reactions. Oxygen-dependent enzymes evolved in ancestrally anaerobic pathways for essential cofactor biosynthesis including NAD+, pyridoxal, thiamine, ubiquinone, cobalamin, heme, and chlorophyll. These innovations allowed prokaryotes to synthesize essential cofactors in O2-containing environments, a prerequisite for the later emergence of aerobic respiratory chains.

A prebiotic Krebs cycle analog generates amino acids with H2 and NH3 over nickel.

Hydrogen (H2) has powered microbial metabolism for roughly 4 billion years. The recent discovery that it also fuels geochemical analogs of the most ancient biological carbon fixation pathway sheds light on the origin of metabolism. However, it remains unclear whether H2 can sustain more complex nonenzymatic reaction networks. Here, we show that H2 drives the nonenzymatic reductive amination of six biological ketoacids and glyoxylate to give the corresponding amino acids in good yields using ammonium concentrations ranging from 6 to 150 mM. Catalytic amounts of nickel or ground meteorites enable these reactions at 22°C and pH 8. The same conditions promote an H2-dependent ketoacid-forming reductive aldol chemistry that co-occurs with reductive amination, producing a continuous reaction network resembling amino acid synthesis in the metabolic core of ancient microbes. The results support the hypothesis that the earliest biochemical networks could have emerged without enzymes or RNA.

Individual and population-level variability in HLA-DR associated immunogenicity risk of biologics used for the treatment of rheumatoid arthritis.

Hypothesis: While conventional in silico immunogenicity risk assessments focus on measuring immunogenicity based on the potential of therapeutic proteins to be processed and presented by a global population-wide set of human leukocyte antigen (HLA) alleles to T cells, future refinements might adjust for HLA allele frequencies in different geographic regions or populations, as well for as individuals in those populations. Adjustment by HLA allele distribution may reveal risk patterns that are specific to population groups or individuals, which current methods that rely on global-population HLA prevalence may obscure. Key findings: This analysis uses HLA frequency-weighted binding predictions to define immunogenicity risk for global and sub-global populations. A comparison of assessments tuned for North American/European versus Japanese/Asian populations suggests that the potential for anti-therapeutic responses (anti-therapeutic antibodies or ATA) for several commonly prescribed Rheumatoid Arthritis (RA) therapeutic biologics may differ, significantly, between the Caucasian and Japanese populations. This appears to align with reports of differing product-related immunogenicity that is observed in different populations. Relevance to clinical practice: Further definition of population-level (regional) and individual patient-specific immunogenic risk profiles may enable prescription of the RA therapeutic with the highest probability of success to each patient, depending on their population of origin and/or their individual HLA background. Furthermore, HLA-specific immunogenicity outcomes data are limited, thus there is a need to expand HLA-association studies that examine the relationship between HLA haplotype and ATA in the clinic.

Edge Functionalization of Bulk γ-Graphyne Facilitates Mechanical Exfoliation and Modulates the Mode of Sheet Stacking.

We have successfully achieved selective and efficient functionalization of sheet edges in microcrystalline multilayer γ-graphyne through two methods: cross-coupling with residual bromide edge groups and copper-catalyzed azide-alkyne cycloaddition (CuAAC) with edge terminal alkyne groups. This modification significantly enhances the ease of mechanical exfoliation and dispersibility of the sheets of γ-graphyne. Specifically, C18-grafted γ-graphyne forms stable dispersions in compatible organic solvents, allowing for the imaging of atomically thin layers of γ-graphyne for the first time. Additionally, we have discovered that phenylacetylide edge groups alter the preferred stacking mode of γ-graphyne sheets. Few-layer flakes of Ph-edge γ-graphyne exhibit a preference for the R3m space group, contrasting with the aperiodic stacking of Br-edge γ-graphyne. These results open the door for scalable exfoliation of few-layer flakes of γ-graphyne with a high aspect ratio, enabling potential applications in carbon electronics.

Bone-Level Tapered Implants for Single Tooth Replacement: Immediate vs Delayed Placement-A Multicenter Randomized Controlled, 1-Year, Non-inferiority Clinical Study.

PURPOSE: To compare the outcomes of immediate and delayed implant placement with bone-level tapered implants. MATERIALS AND METHODS: In this post-market, multicenter prospective randomized controlled study with a primary endpoint of 1 year, 53 patients were randomized to receive either immediate implant placement (test group) or delayed implant placement (control group). The mean crestal bone level changes from implant loading to 12 months postloading were measured using standardized digital periapical radiographs. Changes in facial plate thickness (as measured on CBCT images), implant success and survival, implant stability, soft tissue changes, patient-centered outcomes, and adverse events were measured to assess outcomes between the test and control treatments at 12 months postloading. RESULTS: Of the original 53 patients, 46 patients completed the study (23 in each group). Mean bone changes from loading to the 12-month follow-up were recorded with no statistically significant difference (P = .950) between the groups. The hypothesis was confirmed that immediate implant placement (test) in extraction sockets produces in similar outcomes as delayed placement (control). The test group was found to be similar to the control group (P = .022) in terms of mean changes in facial plate thickness. Implant survival and success were 95.8% in the test group and 92% in the control group. Stability in the control group was superior at the time of surgery, but there was no difference between the groups at implant loading, producing a nonsignificant P value of .563). CONCLUSIONS: This randomized controlled multicenter study showed comparable outcomes 1 year after prosthetic loading in the immediate and delayed implant placement groups.

Ferredoxin reduction by hydrogen with iron functions as an evolutionary precursor of flavin-based electron bifurcation.

Autotrophic theories for the origin of metabolism posit that the first cells satisfied their carbon needs from CO2 and were chemolithoautotrophs that obtained their energy and electrons from H2. The acetyl-CoA pathway of CO2 fixation is central to that view because of its antiquity: Among known CO2 fixing pathways it is the only one that is i) exergonic, ii) occurs in both bacteria and archaea, and iii) can be functionally replaced in full by single transition metal catalysts in vitro. In order to operate in cells at a pH close to 7, however, the acetyl-CoA pathway requires complex multi-enzyme systems capable of flavin-based electron bifurcation that reduce low potential ferredoxin-the physiological donor of electrons in the acetyl-CoA pathway-with electrons from H2. How can the acetyl-CoA pathway be primordial if it requires flavin-based electron bifurcation? Here, we show that native iron (Fe0), but not Ni0, Co0, Mo0, NiFe, Ni2Fe, Ni3Fe, or Fe3O4, promotes the H2-dependent reduction of aqueous Clostridium pasteurianum ferredoxin at pH 8.5 or higher within a few hours at 40 °C, providing the physiological function of flavin-based electron bifurcation, but without the help of enzymes or organic redox cofactors. H2-dependent ferredoxin reduction by iron ties primordial ferredoxin reduction and early metabolic evolution to a chemical process in the Earth's crust promoted by solid-state iron, a metal that is still deposited in serpentinizing hydrothermal vents today.

In silico methods for immunogenicity risk assessment and human homology screening for therapeutic antibodies.

In silico immunogenicity risk assessment has been an important step in the development path for many biologic therapeutics, including monoclonal antibodies. Even if the source of a given biologic is 'fully human', T cell epitopes that are contained in the sequences of the biologic may activate the immune system, enabling the development of anti-drug antibodies that can reduce drug efficacy and may contribute to adverse events. Computational tools that identify T cell epitopes from primary amino acid sequences have been used to assess the immunogenic potential of therapeutic candidates for several decades. To facilitate larger scale analyses and accelerate preclinical immunogenicity risk assessment, our group developed an integrated web-based platform called ISPRI, (Immunogenicity Screening and Protein Re-engineering Interface) that provides hands-on access through a secure web-based interface for scientists working in large and mid-sized biotech companies in the US, Europe, and Japan. This toolkit has evolved and now contains an array of algorithms that can be used individually and/or consecutively for immunogenicity assessment and protein engineering. Most analyses start with the advanced epitope mapping tool (EpiMatrix), then proceed to identify epitope clusters using ClustiMer, and then use a tool called JanusMatrix to define whether any of the T cell epitope clusters may generate a regulatory T cell response which may diminish or eliminate anti-drug antibody formation. Candidates can be compared to similar products on a normalized immunogenicity scale. Should modifications to the biologic sequence be an option, a tool for moderating putative immunogenicity by editing T cell epitopes out of the sequence is available (OptiMatrix). Although this perspective discusses the in-silico immunogenicity risk assessment for monoclonal antibodies, bi-specifics, multi-specifics, and antibody-drug conjugates, the analysis of additional therapeutic modalities such as enzyme replacement proteins, blood factor proteins, CAR-T, gene therapy products, and peptide drugs is also made available on the ISPRI platform.

ISPRI (Interactive Screening and Protein Reengineering Interface): Integrated, cloud-based, comprehensive toolkit for Immunogenicity Risk Assessment.EpiMatrix Immunogenicity Score: Combined T effector and Treg Epitope Content per unit protein.Tregitopes: Treg Epitopes found in IgG Framework that have been shown to modulate antigen-specific effector T cell responses.ClustiMer: Tool for identifying epitope rich polypeptides from within a given protein sequence.JanusMatrix: Tool for Predicting Tolerance, Putative Treg Epitopes, and Anti-self-immune responses.OptiMatrix: Tool for modifying T cell epitope sequences to reduce (or enhance) MHC binding.

Cryptic diversity of cellulose-degrading gut bacteria in industrialized humans.

Humans, like all mammals, depend on the gut microbiome for digestion of cellulose, the main component of plant fiber. However, evidence for cellulose fermentation in the human gut is scarce. We have identified ruminococcal species in the gut microbiota of human populations that assemble functional multienzymatic cellulosome structures capable of degrading plant cell wall polysaccharides. One of these species, which is strongly associated with humans, likely originated in the ruminant gut and was subsequently transferred to the human gut, potentially during domestication where it underwent diversification and diet-related adaptation through the acquisition of genes from other gut microbes. Collectively, these species are abundant and widespread among ancient humans, hunter-gatherers, and rural populations but are rare in populations from industrialized societies thus indicating potential disappearance in response to the westernized lifestyle.

Flexural properties and fatigue limit of 3D-printed and milled resin-based materials.

PURPOSE: The purpose of this study was to evaluate the flexural strength (FS), flexural modulus (FM), and fatigue limit (FL) of 3D-printed resin-based polymers and composites and compare them to 3D-printed composites. MATERIALS AND METHODS: A bar-shaped specimen (25 × 2 × 2 mm) was CAD designed according to ISO 4049:2019, and 60 duplicates of the 3D model were nested at a 45-degree angle with the printing platform and 3D-printed with three materials: denture teeth resin (Denture Teeth, Formlabs), temporary crown and bridge resin (Temporary CB, Formlabs), and composite (Flexcera Smile Ultra+, Desktop Health). The 3D model was also imported into a dental CAM software, duplicated 60 times, nested, and milled from a 3D-milled composite puck (Ivotion Denture Teeth, Ivoclar). All specimens were post-processed following the manufacturer's recommendation. The specimens were then subjected to a three-point bending test until failure using a Universal Testing Machine at a crosshead speed of 0.75 mm/min, and FS and FM were calculated. The remaining thirty specimens were tested for Fatigue Limit using the staircase approach starting at 50% FS maximum up to 1.2 M cycles at 10 Hz. The data were analyzed using one-way ANOVA and the Weibull distribution (α = 0.05). RESULTS: The results showed that Ivotion and Flexcera had higher FS (110.3 ± 7.1 MPa and 107.6 ± 6.4 MPa, respectively) and FM (3.3 ± 0.1 GPa and 3.0 ± 0.2 GPa, respectively) compared to the 3D-printed Denture Teeth (FS = 66.4 ± 18.5 MPa and FM = 1.8 ± 0.1 GPa) and Temporary CB (FS = 79.6 ± 12.1 MPa and FM = 2.7 ± 0.4 GPa). Weibull analysis showed that the Ivotion and Flexcera had a more uniform and narrower spatial distribution of defects (m: 27.98 and 29.19) than the printed materials, which had m values of 8.17 and 4.11 for Temporary CB and Denture Teeth, respectively. Although no differences were found in the static properties (FS and FM) between Ivotion and Flexcera, Ivotion presented a higher endurance limit than Flexcera (51.43 vs. 40.95 MPa). The Temporary CB presented 21.08 MPa and Denture Teeth presented 17.80 MPa of endurance limit. CONCLUSIONS: 3D-milled (Ivotion Denture Teeth) and 3D-printed (Flexcera Smile Ultra+) composites outperformed 3D-printed resins (Formlabs Denture Teeth and Temporary Crown & Bridge) in terms of flexural properties and fatigue resistance. 3D-milled (Ivotion) and 3D-printed (Flexcera) composites exhibited similar flexural properties, but 3D-milled composites showed a 25% higher fatigue endurance limit, suggesting improved clinical longevity.

Neoadjuvant personalized cancer vaccines: the final frontier?

INTRODUCTION: Clinical trials of personalized cancer vaccines have shown that on-demand therapies that are manufactured for each patient, result in activated T cell responses against individual tumor neoantigens. However, their use has been traditionally restricted to adjuvant settings and late-stage cancer therapy. There is growing support for the implementation of PCV earlier in the cancer therapy timeline, for reasons that will be discussed in this review. AREAS COVERED: The efficacy of cancer vaccines may be to some extent dependent on treatment(s) given prior to vaccine administration. Tumors can undergo radical immunoediting following treatment with immunotherapies, such as checkpoint inhibitors, which may affect the presence of the very mutations targeted by cancer vaccines. This review will cover the topics of neoantigen cancer vaccines, tumor immunoediting, and therapy timing. EXPERT OPINION: Therapy timing remains a critical topic to address in optimizing the efficacy of personalized cancer vaccines. Most personalized cancer vaccines are being evaluated in late-stage cancer patients and after treatment with checkpoint inhibitors, but they may offer a greater benefit to the patient if administered in earlier clinical settings, such as the neoadjuvant setting, where patients are not facing T cell exhaustion and/or a further compromised immune system.

Effect of proline content and histidine ligation on the dynamics of Ω-loop D and the peroxidase activity of iso-1-cytochrome c.

To study how proline residues affect the dynamics of Ω-loop D (residues 70 to 85) of cytochrome c, we prepared G83P and G83A variants of yeast iso-1-cytochrome c (iso-1-Cytc) in the presence and absence of a K73H mutation. Ω-loop D is important in controlling both the electron transfer function of Cytc and the peroxidase activity of Cytc used in apoptosis because it provides the Met80 heme ligand. The G83P and G83A mutations have no effect on the global stability of iso-1-Cytc in presence or absence of the K73H mutation. However, both mutations destabilize the His73-mediated alkaline conformer relative to the native state. pH jump stopped-flow experiments show that the dynamics of the His73-mediated alkaline transition are significantly enhanced by the G83P mutation. Gated electron transfer studies show that the enhanced dynamics result from an increased rate of return to the native state, whereas the rate of loss of Met80 ligation is unchanged by the G83P mutation. Thus, the G83P substitution does not stiffen the conformation of the native state. Because bis-His heme ligation occurs when Cytc binds to cardiolipin-containing membranes, we studied the effect of His73 ligation on the peroxidase activity of Cytc, which acts as an early signal in apoptosis by causing oxygenation of cardiolipin. We find that the His73 alkaline conformer suppresses the peroxidase activity of Cytc. Thus, the bis-His ligated state of Cytc formed upon binding to cardiolipin is a negative effector for the peroxidase activity of Cytc early in apoptosis.

Optimization of therapeutic antibodies for reduced self-association and non-specific binding via interpretable machine learning.

Antibody development, delivery, and efficacy are influenced by antibody-antigen affinity interactions, off-target interactions that reduce antibody bioavailability and pharmacokinetics, and repulsive self-interactions that increase the stability of concentrated antibody formulations and reduce their corresponding viscosity. Yet identifying antibody variants with optimal combinations of these three types of interactions is challenging. Here we show that interpretable machine-learning classifiers, leveraging antibody structural features descriptive of their variable regions and trained on experimental data for a panel of 80 clinical-stage monoclonal antibodies, can identify antibodies with optimal combinations of low off-target binding in a common physiological-solution condition and low self-association in a common antibody-formulation condition. For three clinical-stage antibodies with suboptimal combinations of off-target binding and self-association, the classifiers predicted variable-region mutations that optimized non-affinity interactions while maintaining high-affinity antibody-antigen interactions. Interpretable machine-learning models may facilitate the optimization of antibody candidates for therapeutic applications.

Indoximod-based chemo-immunotherapy for pediatric brain tumors: A first-in-children phase I trial.

BACKGROUND: Recurrent brain tumors are the leading cause of cancer death in children. Indoleamine 2,3-dioxygenase (IDO) is a targetable metabolic checkpoint that, in preclinical models, inhibits anti-tumor immunity following chemotherapy. METHODS: We conducted a phase I trial (NCT02502708) of the oral IDO-pathway inhibitor indoximod in children with recurrent brain tumors or newly diagnosed diffuse intrinsic pontine glioma (DIPG). Separate dose-finding arms were performed for indoximod in combination with oral temozolomide (200 mg/m2/day x 5 days in 28-day cycles), or with palliative conformal radiation. Blood samples were collected at baseline and monthly for single-cell RNA-sequencing with paired single-cell T cell receptor sequencing. RESULTS: Eighty-one patients were treated with indoximod-based combination therapy. Median follow-up was 52 months (range 39-77 months). Maximum tolerated dose was not reached, and the pediatric dose of indoximod was determined as 19.2 mg/kg/dose, twice daily. Median overall survival was 13.3 months (n = 68, range 0.2-62.7) for all patients with recurrent disease and 14.4 months (n = 13, range 4.7-29.7) for DIPG. The subset of n = 26 patients who showed evidence of objective response (even a partial or mixed response) had over 3-fold longer median OS (25.2 months, range 5.4-61.9, p = 0.006) compared to n = 37 nonresponders (7.3 months, range 0.2-62.7). Four patients remain free of active disease longer than 36 months. Single-cell sequencing confirmed emergence of new circulating CD8 T cell clonotypes with late effector phenotype. CONCLUSIONS: Indoximod was well tolerated and could be safely combined with chemotherapy and radiation. Encouraging preliminary evidence of efficacy supports advancing to Phase II/III trials for pediatric brain tumors.

A Systems Nephrology Approach to Diabetic Kidney Disease Research and Practice.

BACKGROUND: Diagnosis and staging of diabetic kidney disease (DKD) via the serial assessment of routine laboratory indices lacks the granularity required to resolve the heterogeneous disease mechanisms driving progression in the individual patient. A systems nephrology approach may help resolve mechanisms underlying this clinically apparent heterogeneity, paving a way for targeted treatment of DKD. SUMMARY: Given the limited access to kidney tissue in routine clinical care of patients with DKD, data derived from renal tissue in preclinical model systems, including animal and in vitro models, can play a central role in the development of a targeted systems-based approach to DKD. Multi-centre prospective cohort studies, including the Kidney Precision Medicine Project (KPMP) and the European Nephrectomy Biobank (ENBiBA) project, will improve access to human diabetic kidney tissue for research purposes. Integration of diverse data domains from such initiatives including clinical phenotypic data, renal and retinal imaging biomarkers, histopathological and ultrastructural data, and an array of molecular omics (transcriptomics, proteomics, etc.) alongside multi-dimensional data from preclinical modelling offers exciting opportunities to unravel individual-level mechanisms underlying progressive DKD. The application of machine and deep learning approaches may particularly enhance insights derived from imaging and histopathological/ultrastructural data domains. KEY MESSAGES: Integration of data from multiple model systems (in vitro, animal models, and patients) and from diverse domains (clinical phenotypic, imaging, histopathological/ultrastructural, and molecular omics) offers potential to create a precision medicine approach to DKD care wherein the right treatments are offered to the right patients at the right time.