Bibliometric Indices As Indicators of Research Output: Analyzing Anesthesiologists as a Paradigm for Surgical Disciplines.

Anesthesiology is one of the increasingly competitive surgical specialties with a growing emphasis on scholarly activity. A metric of productivity and citation influence, the Hirsch index (h-index), can help identify mentors capable of guiding postgraduate trainees toward successful academic achievements. This study sought to determine associations between h-indices or m-quotients and manuscript publication in anesthesiology. Using the American Society of Anesthesiologists (ASA) website, accepted abstracts from the ASA Annual Meetings from 2019 to 2021 were screened (n=2146). The first author (FAHi) and senior author (SAHi) h-indices, as well as the first author (FAMq) and senior author (SAMq) m-quotients, were collected for each abstract using the Scopus database. Whether an accepted abstract was subsequently published as a manuscript in a peer-reviewed journal was also noted, along with the number of days between ASA presentation and publication date. Linear and logistic regression models were used for statistical analyses. In total, 348 (34.4%) of the 1012 eligible abstracts were published as manuscripts. Mean FAHi, SAHi, FAMq, and SAMq, were significantly higher for accepted ASA abstracts that were later published in peer-reviewed journals compared to accepted abstracts that were not published (p<0.001). FAHi, SAHi, FAMq, and SAMq had significant positive associations with odds of publication (p=0.002; p<0.001; p=0.006; p<0.001, respectively). There was no statistical significance between FAHi, SAHi, FAMq, or SAMq and the number of days between ASA presentation and publication. Our study uniquely demonstrates the positive, direct association between h-indices and m-quotients with the probability of publication in anesthesiology. We propose that bibliometric indices are adapted to provide a refined perspective of a physician-scientist's capabilities. Postgraduate trainees can use these indices to discern research mentors primed to foster academic excellence.

Using Bibliometric Analysis to Map the Impact of a Simulation Program's Published Scholarly Works.

ABSTRACT: Bibliometrics quantitatively evaluates the targeted literature sources and can help define research and scholarly publications' impact and demonstrate connections for authors, departments, or universities. This article presents a methodology for simulation programs to evaluate their influence in terms of both impact and scope of their published simulation-based healthcare scholarly output. Using the authors' home university and healthcare system as an example, the article outlines a methodology to map research and scholarly works networks within the systems, identify and map connections outside the system, and quantifiably score the overall impact of the simulation program's scholarly output using a common scoring metric, the h-index. This generates an objective measure of impact, rather than a subjective opinion of an organization's research and scholarly impact. The combination of an institutional h-index with mapping of simulation-based healthcare scholarly output provides a full, objective description of the institution's output and provides a benchmark for other simulation programs for comparison.

A General Mechanism for the General Stress Response in Bacteria.

Bacteria have a widely conserved General Stress Response (GSR) that allows them to survive adverse environmental conditions. However, because the signaling proteins that initiate the GSR have evolved to respond to a vast range of species-specific signals, we lack a general understanding of how they are controlled. Here, we determined the molecular mechanism by which a member of the PPM family of protein serine/threonine phosphatases, RsbU, activates the GSR in B. subtilis. It was known that the phosphatase activity of RsbU is activated through interaction with a partner protein, RsbT, when it is released from a megadalton stress-sensing complex upon environmental stress, but how RsbT activates RsbU was not understood. Here we report that RsbT binds an otherwise flexible linker of RsbU to dimerize and activate its phosphatase domains through a conserved allosteric switch element. Conformational flexibility of the homologous linker was known to control activity of the E. coli GSR-activating protein (RssB), which lacks phosphatase activity and functions as a protease adapter protein, suggesting a unifying model for GSR activation across bacterial phyla. Furthermore, and as we now show, the crossing α-helical conformation of RsbU linkers in the active dimeric state is similar to that predicted for paralogous bacterial phosphatases with diverse N-terminal sensory domains, and to linkers known to control the activity of GGDEF diguanylate cyclases and histidine kinases. We propose that this shared regulatory mechanism provides a modularly exchangeable toolkit for bacteria to recognize diverse environmental signals.

Targeted Temperature Management for Patients with Acute Ischemic Stroke: A Literature Review.

Despite significant advances in medical imaging, thrombolytic therapy, and mechanical thrombectomy, acute ischemic strokes (AIS) remain a major cause of mortality and morbidity globally. Targeted temperature management (TTM) has emerged as a potential therapeutic intervention, aiming to mitigate neuronal damage and improve outcomes. This literature review examines the efficacy and challenges of TTM in the context of an AIS. A comprehensive literature search was conducted using databases such as PubMed, Cochrane, Web of Science, and Google Scholar. Studies were selected based on relevance and quality. We identified key factors influencing the effectiveness of TTM such as its timing, depth and duration, and method of application. The review also highlighted challenges associated with TTM, including increased pneumonia rates. The target temperature range was typically between 32 and 36 °C, with the duration of cooling from 24 to 72 h. Early initiation of TTM was associated with better outcomes, with optimal results observed when TTM was started within the first 6 h post-stroke. Emerging evidence indicates that TTM shows considerable potential as an adjunctive treatment for AIS when implemented promptly and with precision, thereby potentially mitigating neuronal damage and enhancing overall patient outcomes. However, its application is complex and requires the careful consideration of various factors.

Subdomain dynamics enable chemical chain reactions in non-ribosomal peptide synthetases.

Many peptide-derived natural products are produced by non-ribosomal peptide synthetases (NRPSs) in an assembly-line fashion. Each amino acid is coupled to a designated peptidyl carrier protein (PCP) through two distinct reactions catalysed sequentially by the single active site of the adenylation domain (A-domain). Accumulating evidence suggests that large-amplitude structural changes occur in different NRPS states; yet how these molecular machines orchestrate such biochemical sequences has remained elusive. Here, using single-molecule Förster resonance energy transfer, we show that the A-domain of gramicidin S synthetase I adopts structurally extended and functionally obligatory conformations for alternating between adenylation and thioester-formation structures during enzymatic cycles. Complementary biochemical, computational and small-angle X-ray scattering studies reveal interconversion among these three conformations as intrinsic and hierarchical where intra-A-domain organizations propagate to remodel inter-A-PCP didomain configurations during catalysis. The tight kinetic coupling between structural transitions and enzymatic transformations is quantified, and how the gramicidin S synthetase I A-domain utilizes its inherent conformational dynamics to drive directional biosynthesis with a flexibly linked PCP domain is revealed.

Development and Evaluation of Aeyeconsult: A Novel Ophthalmology Chatbot Leveraging Verified Textbook Knowledge and GPT-4.

OBJECTIVE: There has been much excitement on the use of large language models (LLMs) such as ChatGPT in ophthalmology. However, LLMs are limited in that they are trained on unverified information and do not cite their sources. This paper highlights a new methodology to create a generative AI chatbot to answer eye care related questions which uses only verified ophthalmology textbooks as data and cites its sources. SETTING: Yale School of Medicine Department of Ophthalmology and Visual Science. DESIGN/METHODS: Aeyeconsult, an ophthalmology chatbot, was developed using GPT-4 (the LLM used to power the publicly available chatbot ChatGPT-4), LangChain, and Pinecone. Ophthalmology textbooks were processed into embeddings and stored in Pinecone. User queries were similarly converted, compared to stored embeddings, and GPT-4 generated responses. The interface was adapted from public code. Both Aeyeconsult and ChatGPT-4 were tested on the same 260 questions from OphthoQuestions.com, with the first response from Aeyeconsult and ChatGPT-4 recorded as the answer. RESULTS: Aeyeconsult outperformed ChatGPT-4 on the OKAP dataset, with 83.4% correct answers compared to 69.2% (p = 0.0118). Aeyeconsult also had fewer instances of no answer and multiple answers. Both systems performed best in General Medicine, with Aeyeconsult achieving 96.2% accuracy. Aeyeconsult's weakest performance was in Clinical Optics at 68.1%, but it still outperformed ChatGPT-4 in this category (45.5%). CONCLUSION: LLMs may be useful in answering ophthalmology questions but their trustworthiness and accuracy is limited due to training on unverified internet data and lack of source citation. We used a new methodology, using verified ophthalmology textbooks as source material and providing citations, to mitigate these issues, resulting in a chatbot more accurate than ChatGPT-4 in answering OKAPs style questions.

Data science competition for cross-site individual tree species identification from airborne remote sensing data.

Data on individual tree crowns from remote sensing have the potential to advance forest ecology by providing information about forest composition and structure with a continuous spatial coverage over large spatial extents. Classifying individual trees to their taxonomic species over large regions from remote sensing data is challenging. Methods to classify individual species are often accurate for common species, but perform poorly for less common species and when applied to new sites. We ran a data science competition to help identify effective methods for the task of classification of individual crowns to species identity. The competition included data from three sites to assess each methods' ability to generalize patterns across two sites simultaneously and apply methods to an untrained site. Three different metrics were used to assess and compare model performance. Six teams participated, representing four countries and nine individuals. The highest performing method from a previous competition in 2017 was applied and used as a baseline to understand advancements and changes in successful methods. The best species classification method was based on a two-stage fully connected neural network that significantly outperformed the baseline random forest and gradient boosting ensemble methods. All methods generalized well by showing relatively strong performance on the trained sites (accuracy = 0.46-0.55, macro F1 = 0.09-0.32, cross entropy loss = 2.4-9.2), but generally failed to transfer effectively to the untrained site (accuracy = 0.07-0.32, macro F1 = 0.02-0.18, cross entropy loss = 2.8-16.3). Classification performance was influenced by the number of samples with species labels available for training, with most methods predicting common species at the training sites well (maximum F1 score of 0.86) relative to the uncommon species where none were predicted. Classification errors were most common between species in the same genus and different species that occur in the same habitat. Most methods performed better than the baseline in detecting if a species was not in the training data by predicting an untrained mixed-species class, especially in the untrained site. This work has highlighted that data science competitions can encourage advancement of methods, particularly by bringing in new people from outside the focal discipline, and by providing an open dataset and evaluation criteria from which participants can learn.

INDIVIDUAL ARTICLE: NECOM 3: A Practical Algorithm for the Management of Radiation Therapy-Related Acute Radiation Dermatitis.

BACKGROUND: In the Nordic European countries in 2020, cancer diagnoses accounted for 175,925 patients. About 50% of cancer patients receive radiation therapy (RT), which may lead to radiation dermatitis (RD). Notably, patients with breast, head, neck, and anal cancers may be prone to developing RD. However, few algorithms exist for the prevention and treatment of RD. METHODS: The Nordic European Cutaneous Oncodermatology Management (NECOM) project aims to improve cancer patient outcomes by offering tools to prevent and treat cancer therapy-related cutaneous adverse events (cAEs). The first 2 NECOM papers presented various cAEs and skincare regimens involving hygiene, moisturization, sun protection, and camouflage products for preventing and managing cAEs. The NECOM 3 practical algorithm for preventing and managing acute RD (ARD) is intended to promote healthy skin and reduce RT-related ARD, improving cancer patient outcomes.  Results: The NECOM advisors discussed the results of a systematic literature review and obtained consensus on the evidence and opinion-based practical algorithm for ARD to support all stakeholders in the Nordic European healthcare setting. The algorithm starts with skin-preserving therapy, followed by skin condition assessment and patient-specific interventions based on the grade of RD present.  Conclusion: ARD may lead to symptoms of pruritus and pain, decreased QoL and morbidity, and treatment interruptions. Patient education on the prevention of RD and treatment recommendations given in the NECOM 3 algorithm may help prevent and manage RD and improve the overall care of patients receiving RT. J Drugs Dermatol. 2023;22:11(Suppl 2):s3-s10.

Propofol-Based Anesthesia Maintenance and/or Volatile Anesthetics during Intracranial Aneurysm Repair: A Comparative Analysis of Neurological Outcomes.

BACKGROUND: Volatile and intravenous anesthetics have substantial effects on physiological functions, notably influencing neurological function and susceptibility to injury. Despite the importance of the anesthetic approach, data on its relative risks or benefits during surgical clipping or endovascular treatments for unruptured intracranial aneurysms (UIAs) remains scant. We investigated whether using volatile anesthetics alone or in combination with propofol infusion yields superior neurological outcomes following UIA obliteration. METHODS: We retrospectively reviewed 1001 patients who underwent open or endovascular treatment for UIA, of whom 596 had short- and long-term neurological outcome data (modified Rankin Scale) recorded. Multivariable ordinal regression analysis was performed to examine the association between the anesthetic approach and outcomes. RESULTS: Of 1001 patients, 765 received volatile anesthetics alone, while 236 received propofol infusion and volatile anesthetics (combined anesthetic group). Short-term neurological outcome data were available for 619 patients and long-term data for 596. No significant correlation was found between the anesthetic approach and neurologic outcomes, irrespective of the type of procedure (open craniotomy or endovascular treatment). The combined anesthetic group had a higher rate of ICU admission (p < 0.001) and longer ICU and hospital length of stay (LOS, p < 0.001). Similarly, a subgroup analysis revealed longer ICU and hospital LOS (p < 0.0001 and p < 0.001, respectively) in patients who underwent endovascular UIA obliteration under a combined anesthetic approach (n = 678). CONCLUSIONS: The addition of propofol to volatile anesthetics during UIA obliteration does not provide short- or long-term benefits to neurologic outcomes. Compared to volatile anesthetics alone, the combination of propofol and volatile anesthetics may be associated with an increased rate of ICU admission, as well as longer ICU and hospital LOS.

Structural and functional studies reveal the molecular basis of substrate promiscuity of a glycosyltransferase originating from a major agricultural pest.

The two-spotted spider mite, Tetranychus urticae, is a major cosmopolitan pest that feeds on more than 1100 plant species. Its genome contains an unprecedentedly large number of genes involved in detoxifying and transporting xenobiotics, including 80 genes that code for UDP glycosyltransferases (UGTs). These enzymes were acquired via horizontal gene transfer from bacteria after loss in the Chelicerata lineage. UGTs are well-known for their role in phase II metabolism; however, their contribution to host adaptation and acaricide resistance in arthropods, such as T. urticae, is not yet resolved. TuUGT202A2 (Tetur22g00270) has been linked to the ability of this pest to adapt to tomato plants. Moreover, it was shown that this enzyme can glycosylate a wide range of flavonoids. To understand this relationship at the molecular level, structural, functional, and computational studies were performed. Structural studies provided specific snapshots of the enzyme in different catalytically relevant stages. The crystal structure of TuUGT202A2 in complex with UDP-glucose was obtained and site-directed mutagenesis paired with molecular dynamic simulations revealed a novel lid-like mechanism involved in the binding of the activated sugar donor. Two additional TuUGT202A2 crystal complexes, UDP-(S)-naringenin and UDP-naringin, demonstrated that this enzyme has a highly plastic and open-ended acceptor-binding site. Overall, this work reveals the molecular basis of substrate promiscuity of TuUGT202A2 and provides novel insights into the structural mechanism of UGTs catalysis.

Autoimmune PaneLs as PrEdictors of Toxicity in Patients TReated with Immune Checkpoint InhibiTors (ALERT).

BACKGROUND: Immune-checkpoint inhibitors (ICI) can lead to immune-related adverse events (irAEs) in a significant proportion of patients. The mechanisms underlying irAEs development are mostly unknown and might involve multiple immune effectors, such as T cells, B cells and autoantibodies (AutoAb). METHODS: We used custom autoantigen (AutoAg) microarrays to profile AutoAb related to irAEs in patients receiving ICI. Plasma was collected before and after ICI from cancer patients participating in two clinical trials (NCT03686202, NCT02644369). A one-time collection was obtained from healthy controls for comparison. Custom arrays with 162 autoAg were used to detect IgG and IgM reactivities. Differences of median fluorescent intensity (MFI) were analyzed with Wilcoxon sign rank test and Kruskal-Wallis test. MFI 500 was used as threshold to define autoAb reactivity. RESULTS: A total of 114 patients and 14 healthy controls were included in this study. irAEs of grade (G) ≥ 2 occurred in 37/114 patients (32%). We observed a greater number of IgG and IgM reactivities in pre-ICI collections from patients versus healthy controls (62 vs 32 p < 0.001). Patients experiencing irAEs G ≥ 2 demonstrated pre-ICI IgG reactivity to a greater number of AutoAg than patients who did not develop irAEs (39 vs 33 p = 0.040). We observed post-treatment increase of IgM reactivities in subjects experiencing irAEs G ≥ 2 (29 vs 35, p = 0.021) and a decrease of IgG levels after steroids (38 vs 28, p = 0.009). CONCLUSIONS: Overall, these results support the potential role of autoAb in irAEs etiology and evolution. A prospective study is ongoing to validate our findings (NCT04107311).

The PALB2 DNA-binding domain is an intrinsically disordered recombinase.

The Partner and Localizer of BRCA2 (PALB2) tumor suppressor is a scaffold protein that links BRCA1 with BRCA2 to initiate homologous recombination (HR). PALB2 interaction with DNA strongly enhances HR efficiency. The PALB2 DNA-binding domain (PALB2-DBD) supports DNA strand exchange, a complex multistep reaction supported by only a few protein families such as RecA-like recombinases or Rad52. The mechanisms of PALB2 DNA binding and strand exchange are unknown. We performed circular dichroism, electron paramagnetic spectroscopy, and small-angle X-ray scattering analyses and determined that PALB2-DBD is intrinsically disordered, even when bound to DNA. The intrinsically disordered nature of this domain was further supported by bioinformatics analysis. Intrinsically disordered proteins (IDPs) are prevalent in the human proteome and have many important biological functions. The complexity of the strand exchange reaction significantly expands the functional repertoire of IDPs. The results of confocal single-molecule FRET indicated that PALB2-DBD binding leads to oligomerization-dependent DNA compaction. We hypothesize that PALB2-DBD uses a chaperone-like mechanism to aid formation and resolution of complex DNA and RNA multichain intermediates during DNA replication and repair. Since PALB2-DBD alone or within the full-length PALB2 is predicted to have strong liquid-liquid phase separation (LLPS) potential, protein-nucleic acids condensates are likely to play a role in complex functionality of PALB2-DBD. Similar DNA-binding intrinsically disordered regions may represent a novel class of functional domains that evolved to function in eukaryotic nucleic acid metabolism complexes.

Comparative mucomic analysis of three functionally distinct Cornu aspersum Secretions.

Every animal secretes mucus, placing them among the most diverse biological materials. Mucus hydrogels are complex mixtures of water, ions, carbohydrates, and proteins. Uncertainty surrounding their composition and how interactions between components contribute to mucus function complicates efforts to exploit their properties. There is substantial interest in commercializing mucus from the garden snail, Cornu aspersum, for skincare, drug delivery, tissue engineering, and composite materials. C. aspersum secretes three mucus-one shielding the animal from environmental threats, one adhesive mucus from the pedal surface of the foot, and another pedal mucus that is lubricating. It remains a mystery how compositional differences account for their substantially different properties. Here, we characterize mucus proteins, glycosylation, ion content, and mechanical properties that could be used to provide insight into structure-function relationships through an integrative "mucomics" approach. We identify macromolecular components of these hydrogels, including a previously unreported protein class termed Conserved Anterior Mollusk Proteins (CAMPs). Revealing differences between C. aspersum mucus shows how considering structure at all levels can inform the design of mucus-inspired materials.

Biomimetic human skin model patterned with rete ridges.

Rete ridges consist of undulations between the epidermis and dermis that enhance the mechanical properties and biological function of human skin. However, most human skin models are fabricated with a flat interface between the epidermal and dermal layers. Here, we report a micro-stamping method for producing human skin models patterned with rete ridges of controlled geometry. To mitigate keratinocyte-induced matrix degradation, telocollagen-fibrin matrices with and without crosslinks enable these micropatterned features to persist during longitudinal culture. Our human skin model exhibits an epidermis that includes the following markers: cytokeratin 14, p63, and Ki67 in the basal layer, cytokeratin 10 in the suprabasal layer, and laminin and collagen IV in the basement membrane. We demonstrated that two keratinocyte cell lines, one from a neonatal donor and another from an adult diabetic donor, are compatible with this model. We tested this model using an irritation test and showed that the epidermis prevents rapid penetration of sodium dodecyl sulfate. Gene expression analysis revealed differences in keratinocytes obtained from the two donors as well as between 2D (control) and 3D culture conditions. Our human skin model may find potential application for drug and cosmetic testing, disease and wound healing modeling, and aging studies.

Development of a Robust Consensus Modeling Approach for Identifying Cellular and Media Metabolites Predictive of Mesenchymal Stromal Cell Potency.

Mesenchymal stromal cells (MSCs) have shown promise in regenerative medicine applications due in part to their ability to modulate immune cells. However, MSCs demonstrate significant functional heterogeneity in terms of their immunomodulatory function because of differences in MSC donor/tissue source, as well as non-standardized manufacturing approaches. As MSC metabolism plays a critical role in their ability to expand to therapeutic numbers ex vivo, we comprehensively profiled intracellular and extracellular metabolites throughout the expansion process to identify predictors of immunomodulatory function (T-cell modulation and indoleamine-2,3-dehydrogenase (IDO) activity). Here, we profiled media metabolites in a non-destructive manner through daily sampling and nuclear magnetic resonance (NMR), as well as MSC intracellular metabolites at the end of expansion using mass spectrometry (MS). Using a robust consensus machine learning approach, we were able to identify panels of metabolites predictive of MSC immunomodulatory function for 10 independent MSC lines. This approach consisted of identifying metabolites in 2 or more machine learning models and then building consensus models based on these consensus metabolite panels. Consensus intracellular metabolites with high predictive value included multiple lipid classes (such as phosphatidylcholines, phosphatidylethanolamines, and sphingomyelins) while consensus media metabolites included proline, phenylalanine, and pyruvate. Pathway enrichment identified metabolic pathways significantly associated with MSC function such as sphingolipid signaling and metabolism, arginine and proline metabolism, and autophagy. Overall, this work establishes a generalizable framework for identifying consensus predictive metabolites that predict MSC function, as well as guiding future MSC manufacturing efforts through identification of high-potency MSC lines and metabolic engineering.

The PALB2 DNA-binding domain is an intrinsically disordered recombinase.

The Partner and Localizer of BRCA2 (PALB2) tumor suppressor is a scaffold protein that links BRCA1 with BRCA2 to initiate homologous recombination (HR). PALB2 interaction with DNA strongly enhances HR efficiency. The PALB2 DNA-binding domain (PALB2-DBD) supports DNA strand exchange, a complex multistep reaction supported by only a few protein families such as RecA-like recombinases or Rad52. The mechanisms of PALB2 DNA binding and strand exchange are unknown. We performed circular dichroism, electron paramagnetic spectroscopy, and small-angle X-ray scattering analyses and determined that PALB2-DBD is intrinsically disordered, even when bound to DNA. The intrinsically disordered nature of this domain was further supported by bioinformatics analysis. Intrinsically disordered proteins (IDPs) are prevalent in the human proteome and have many important biological functions. The complexity of the strand exchange reaction significantly expands the functional repertoire of IDPs. The results of confocal single-molecule FRET indicated that PALB2-DBD binding leads to oligomerization-dependent DNA compaction. We hypothesize that PALB2-DBD uses a chaperone-like mechanism to aid formation and resolution of complex DNA and RNA multichain intermediates during DNA replication and repair. Since PALB2-DBD alone or within the full-length PALB2 is predicted to have strong liquid-liquid phase separation (LLPS) potential, protein-nucleic acids condensates are likely to play a role in complex functionality of PALB2-DBD. Similar DNA-binding intrinsically disordered regions may represent a novel class of functional domains that evolved to function in eukaryotic nucleic acid metabolism complexes.

Conformational switching and flexibility in cobalamin-dependent methionine synthase studied by small-angle X-ray scattering and cryoelectron microscopy.

Cobalamin-dependent methionine synthase (MetH) catalyzes the synthesis of methionine from homocysteine and 5-methyltetrahydrofolate (CH3-H4folate) using the unique chemistry of its cofactor. In doing so, MetH links the cycling of S-adenosylmethionine with the folate cycle in one-carbon metabolism. Extensive biochemical and structural studies on Escherichia coli MetH have shown that this flexible, multidomain enzyme adopts two major conformations to prevent a futile cycle of methionine production and consumption. However, as MetH is highly dynamic as well as both a photosensitive and oxygen-sensitive metalloenzyme, it poses special challenges for structural studies, and existing structures have necessarily come from a "divide and conquer" approach. In this study, we investigate E. coli MetH and a thermophilic homolog from Thermus filiformis using small-angle X-ray scattering (SAXS), single-particle cryoelectron microscopy (cryo-EM), and extensive analysis of the AlphaFold2 database to present a structural description of the full-length MetH in its entirety. Using SAXS, we describe a common resting-state conformation shared by both active and inactive oxidation states of MetH and the roles of CH3-H4folate and flavodoxin in initiating turnover and reactivation. By combining SAXS with a 3.6-Å cryo-EM structure of the T. filiformis MetH, we show that the resting-state conformation consists of a stable arrangement of the catalytic domains that is linked to a highly mobile reactivation domain. Finally, by combining AlphaFold2-guided sequence analysis and our experimental findings, we propose a general model for functional switching in MetH.

Detection of novel therapies using a multi-national, multi-institutional registry of cutaneous immune-related adverse events and management.

BACKGROUND: Cutaneous immune-related adverse events (cirAEs) remain a prevalent and common sequelae of immune checkpoint inhibitor (ICI) therapy, often necessitating treatment interruption and prolonged immune suppression. Treatment algorithms are still poorly defined, based on single-institution case reports without adequate safety assessments, and subject to publication bias. METHODS: Data in this registry were collected through a standardized REDCap form distributed to dermatologists via email listserv. RESULTS: Ninety-seven cirAEs were reported from 13 institutions in this registry. Topical and systemic steroids were the most common treatments used; however, targeted treatment matched to disease morphology was identified at numerous sites. Novel cirAE therapy uses that to our knowledge have not been previously described were captured including tacrolimus for the treatment of follicular, bullous, and eczematous eruptions and phototherapy for eczematous eruptions. Moreover, further evidence of cirAE treatment applications sparsely described in literature were also captured in this study including dupilumab and rituximab for bullous eruptions, phototherapy for lichenoid and psoriasiform eruptions, and acitretin for psoriasiform eruptions, among others. No serious adverse events were reported. Numerous targeted therapeutics including dupilumab, rituximab, and psoriasis biologics, among others, were associated with a cirAE grade improvement of ≥2 grades in every patient treated. CONCLUSION: This study suggests that a multi-institutional registry of cirAEs and management is not only feasible but that the information collected can be used to detect, evaluate, and rigorously assess targeted treatments for cirAEs. Further expansion and modification to include treatment progression may allow for sufficient data for specific treatment recommendations to be made.

Improving accuracy of quantifying nitrate removal performance and enhancing understanding of processes in woodchip bioreactors using high-frequency data.

Woodchip bioreactors have gained popularity in many countries as a conservation practice for reducing nitrate load to freshwater. However, current methods for assessing their performance may be inadequate when nitrate removal rates (RR) are determined from low-frequency (e.g., weekly) concurrent sampling at the inlet and outlet. We hypothesised that high-frequency monitoring data at multiple locations can help improve the accuracy of quantifying nitrate removal performance, enhance the understanding of processes occurring within a bioreactor, and therefore improve the design practice for bioreactors. Accordingly, the objectives of this study were to compare RRs calculated using high- and low-frequency sampling and assess the spatiotemporal variability of the nitrate removal within a bioreactor to unravel the processes occurring within a bioreactor. For two drainage seasons, we monitored nitrate concentrations at 21 locations on an hourly or two-hourly basis within a pilot-scale woodchip bioreactor in Tatuanui, New Zealand. A novel method was developed to account for the variable lag time between entry and exit of a parcel of sampled drainage water. Our results showed that this method not only enabled lag time to be accounted for but also helped quantify volumetric inefficiencies (e.g., dead zone) within the bioreactor. The average RR calculated using this method was significantly higher than the average RR calculated using conventional low-frequency methods. The average RRs of each of the quarter sections within the bioreactor were found to be different. 1-D transport modelling confirmed the effect of nitrate loading on the removal process as nitrate reduction followed Michaelis-Menten (MM) kinetics. These results demonstrate that high-frequency temporal and spatial monitoring of nitrate concentrations in the field allows improved description of bioreactor performance and better understanding of processes occurring within woodchip bioreactors. Thus, insights gained from this study can be used to optimise the design of future field bioreactors.

Plasma hydrogen sulfide, nitric oxide, and thiocyanate levels are lower during pregnancy compared to postpartum in a cohort of women from the Pacific northwest of the United States.

AIMS: Pregnancy alters multiple physiological processes including angiogenesis, vasodilation, inflammation, and cellular redox, which are partially modulated by the gasotransmitters hydrogen sulfide (H2S) and nitric oxide (NO). In this study, we sought to determine how plasma levels of H2S, NO, and the H2S-related metabolites thiocyanate (SCN-), and methanethiol (CH3SH) change during pregnancy progression. MATERIALS AND METHODS: Plasma was collected from 45 women at three points: 25-28 weeks gestation, 28-32 week gestation, and at ≥3 months postpartum. Plasma levels of H2S, SCN-, and CH3SH were measured following derivatization using monobromobimane followed by LC-MS/MS. Plasma NO was measured indirectly using the Griess reagent. KEY FINDINGS: NO and SCN- were significantly lower in women at 25-28 weeks gestation and 28-32 weeks gestation than postpartum while plasma H2S levels were significantly lower at 28-32 weeks gestation than postpartum. No significant differences were observed in CH3SH. SIGNIFICANCE: Previous reports demonstrated that the production of H2S and NO are stimulated during pregnancy, but we observed lower levels during pregnancy compared to postpartum. Previous reports on NO have been mixed, but given the related effects of H2S and NO, it is expected that their levels would be higher during pregnancy vs. postpartum. Future studies determining the mechanism for decreased H2S and NO during pregnancy will elucidate the role of these gasotransmitters during normal and pathological progression of pregnancy.