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ABSTRACT Rational engineering of gas-fermenting bacteria for high yields of bioproducts is vital for a sustainable bioeconomy. It will allow the microbial chassis to renewably valorize natural resources from carbon oxides, hydrogen, and/or lignocellulosic feedstocks more efficiently. To date, rational design of gas-fermenting bacteria such as changing the expression levels of individual enzymes to obtain the desired pathway flux is challenging, because pathway design must follow a verifiable metabolic blueprint indicating where interventions should be executed. Based on recent advances in constraint-based thermodynamic and kinetic models, we identify key enzymes in the gas-fermenting acetogen Clostridium ljungdahlii that correlate with the production of isopropanol. To this extent, we integrated a metabolic model in comparison with proteomics measurements and quantified the uncertainty for a variety of pathway targets needed to improve the bioproduction of isopropanol. Based on in silico thermodynamic optimization, minimal protein requirement analysis, and ensemble modeling-based robustness analysis, we identified the top two significant flux control sites, i.e., acetoacetyl-coenzyme A (CoA) transferase (AACT) and acetoacetate decarboxylase (AADC), overexpression of which could lead to increased isopropanol production. Our predictions directed iterative pathway construction, which enabled a 2.8-fold increase in isopropanol production compared to the initial version. The engineered strain was further tested under gas-fermenting mixotrophic conditions, where more than 4 g/L isopropanol was produced when CO, CO2, and fructose were provided as the substrates. In a bioreactor environment sparging with CO, CO2, and H2 only, the strain produced 2.4 g/L isopropanol. Our work highlighted that the gas-fermenting chasses can be fine-tuned for high-yield bioproduction by directed and elaborative pathway engineering. IMPORTANCE Highly efficient bioproduction from gaseous substrates (e.g., hydrogen and carbon oxides) will require systematic optimization of the host microbes. To date, the rational redesign of gas-fermenting bacteria is still in its infancy, due in part to the lack of quantitative and precise metabolic knowledge that can direct strain engineering. Here, we provide a case study by engineering isopropanol production in gas-fermenting Clostridium ljungdahlii. We demonstrate that a modeling approach based on the thermodynamic and kinetic analysis at the pathway level can provide actionable insights into strain engineering for optimal bioproduction. This approach may pave the way for iterative microbe redesign for the conversion of renewable gaseous feedstocks.

3-Hydroxybutyrate (3HB) is a product of interest as it is a precursor to the commercially produced bioplastic polyhydroxybutyrate. It can also serve as a platform for fine chemicals, medicines, and biofuels, making it a value-added product and feedstock. Acetogens non-photosynthetically fix CO2 into acetyl-CoA and have been previously engineered to convert acetyl-CoA into 3HB. However, as acetogen metabolism is poorly understood, those engineering efforts have had varying levels of success. 3HB, using acetyl-CoA as a precursor, can be synthesized by a variety of different pathways. Here we systematically compare various pathways to produce 3HB in acetogens and discover a native (S)-3-hydroxybutyryl-CoA dehydrogenase, hbd2, responsible for endogenous 3HB production. In conjunction with the heterologous thiolase atoB and CoA transferase ctfAB, hbd2 overexpression improves yields of 3HB on both sugar and syngas (CO/H2/CO2), outperforming the other tested pathways. These results uncovered a previously unknown 3HB production pathway, inform data from prior metabolic engineering efforts, and have implications for future physiological and biotechnological anaerobic research.

The sustainable production of chemicals from non-petrochemical sources is one of the greatest challenges of our time. CO2 release from industrial activity is not environmentally friendly yet provides an inexpensive feedstock for chemical production. One means of addressing this problem is using acetogenic bacteria to produce chemicals from CO2, waste streams, or renewable resources. Acetogens are attractive hosts for chemical production for many reasons: they can utilize a variety of feedstocks that are renewable or currently waste streams, can capture waste carbon sources and covert them to products, and can produce a variety of chemicals with greater carbon efficiency over traditional fermentation technologies. Here we investigated the metabolism of Clostridium ljungdahlii, a model acetogen, to probe carbon and electron partitioning and understand what mechanisms drive product formation in this organism. We utilized CRISPR/Cas9 and an inducible riboswitch to target enzymes involved in fermentation product formation. We focused on the genes encoding phosphotransacetylase (pta), aldehyde ferredoxin oxidoreductases (aor1 and aor2), and bifunctional alcohol/aldehyde dehydrogenases (adhE1 and adhE2) and performed growth studies under a variety of conditions to probe the role of those enzymes in the metabolism. Finally, we demonstrated a switch from acetogenic to ethanologenic metabolism by these manipulations, providing an engineered bacterium with greater application potential in biorefinery industry.

Volumetric muscle defect, caused by trauma or combat injuries, is a major health concern leading to severe morbidity. It is characterized by partial or full thickness loss of muscle and its bio-scaffold, resulting in extensive fibrosis and scar formation. Therefore, the ideal therapeutic option is to use stem cells combined with bio-scaffolds to restore muscle. For this purpose, muscle-derived stem cells (MDSCs) are a great candidate due to their unique multi-lineage differentiation potential.In this study, we evaluated the regeneration potential of MDSCs for muscle loss repair using a novel in situ fibrin gel casting. Muscle defect was created by a partial thickness wedge resection in the tibialis anterior (TA) muscles of NSG mice which created an average of 25% mass loss. If untreated, this defect leads to severe muscle fibrosis. Next, MDSCs were delivered using a novel in situ fibrin gel casting method.Our results demonstrated MDSCs are able to engraft and form new myofibers in the defect when casted along with fibrin gel. LacZ labeled MDSCs were able to differentiate efficiently into new myofibers and significantly increase muscle mass. This was also accompanied by significant reduction of fibrotic tissue in the engrafted muscles. Furthermore, transplanted cells also contributed to new vessel formation and satellite cell seeding.These results confirmed the therapeutic potential of MDSCs and feasibility of direct in situ casting of fibrin/MDSC mixture to repair muscle mass defects. Keywords: Skeletal muscle, Volumetric muscle loss, Fibrin gel, Muscle-derived stem cells (MDSCs), Muscle repair, Bio-scaffold

Recently, a new type of limb-girdle muscular dystrophy (LGMD type 2Z) has been identified due to a missense mutation in POGLUT1 (protein O-glucosyltransferase-Rumi), an enzyme capable of adding glucose to a distinct serine residue of epidermal growth factor-like repeats containing a C-X-S-X-(P/A)-C consensus sequence such as Notch receptors. Affected patients demonstrate reduced Notch signaling, decreased muscle stem cell pool and hypoglycosylation of α-dystroglycan, leading to LGMD phenotype. Here we report the generation and characterization of an iPSC line (CSCRMi001-A) from a LGMD-2Z patient with missense mutation in POGLUT1 which can be used for in vitro disease modeling.

Stable isotope based metabolic flux analysis is currently the unique methodology that allows the experimental study of the integrated responses of metabolic networks. This method primarily relies on isotope labeling and modeling, which could be a challenge in both experimental and computational biology. In particular, the algorithm implementation for isotope simulation is a critical step, limiting extensive usage of this powerful approach. Here, we introduce EMUlator a Python-based isotope simulator which is developed on Elementary Metabolite Unit (EMU) algorithm, an efficient and powerful algorithm for isotope modeling. We propose a novel adjacency matrix method to implement EMU modeling and exemplify it stepwise. This method is intuitively straightforward and can be conveniently mastered for various customized purposes. We apply this arithmetic pipeline to understand the phosphoketolase flux in the metabolic network of an industrial microbe Clostridium acetobutylicum. The resulting design enables a high-throughput and non-invasive approach for estimating phosphoketolase flux in vivo. Our computational insights allow the systematic design and prediction of isotope-based metabolic models and yield a comprehensive understanding of their limitations and potentials.

Summary: Myogenic differentiation of human pluripotent stem cells (hPSCs) has been done by gene overexpression or directed differentiation. However, viral integration, long-term culture, and the presence of unwanted cells are the main obstacles. By using CRISPR/Cas9n, a double-reporter human embryonic stem cell (hESC) line was generated for PAX7/MYF5, allowing prospective readout. This strategy allowed pathway screen to define efficient myogenic induction in hPSCs. Next, surface marker screen allowed identification of CD10 and CD24 for purification of myogenic progenitors and exclusion of non-myogenic cells. CD10 expression was also identified on human satellite cells and skeletal muscle progenitors. In vitro and in vivo studies using transgene and/or reporter-free hPSCs further validated myogenic potential of the cells by formation of new fibers expressing human dystrophin as well as donor-derived satellite cells in NSG-mdx4Cv mice. This study provides biological insights for myogenic differentiation of hPSCs using a double-reporter cell resource and defines an improved myogenic differentiation and purification strategy. : Wu et al. demonstrate that, by generation of a double-reporter human embryonic stem cell line for skeletal muscle lineage, cells can be screened for governing pathways and surface markers, defining myogenic induction and purification protocol and evaluation of their regenerative potential using in vivo studies in a mouse model for muscular dystrophy.

Cellulolytic bacteria have the potential to perform lignocellulose hydrolysis and fermentation simultaneously. The metabolic pathways of these bacteria, therefore, require more comprehensive and quantitative understanding. Using isotope tracer, gas chromatography-mass spectrometry, and metabolic flux modeling, we decipher the metabolic network of Clostridium thermocellum, a model cellulolytic bacterium which represents as an attractive platform for conversion of lignocellulose to dedicated products. We uncover that the Embden–Meyerhof–Parnas (EMP) pathway is the predominant glycolytic route whereas the Entner–Doudoroff (ED) pathway and oxidative pentose phosphate pathway are inactive. We also observe that C. thermocellum's TCA cycle is initiated by both Si- and Re-citrate synthase, and it is disconnected between 2-oxoglutarate and oxaloacetate in the oxidative direction; C. thermocellum uses a citramalate shunt to synthesize isoleucine; and both the one-carbon pathway and the malate shunt are highly active in this bacterium. To gain a quantitative understanding, we further formulate a fluxome map to quantify the metabolic fluxes through central metabolic pathways. This work represents the first global in vivo investigation of the principal carbon metabolism of C. thermocellum. Our results elucidate the unique structure of metabolic network in this cellulolytic bacterium and demonstrate the capability of isotope-assisted metabolite studies in understanding microbial metabolism of industrial interests.

Abstract Methotrexate (MTX) doses on days +1, +3, +6, and +11 after match unrelated donor allogeneic stem cell transplant (MUD HSCT) is a common graft‐versus‐host disease (GVHD) prophylaxis regimen. However, the overlapping toxicity of MTX with conditioning chemotherapy sometimes warrants the omission of the fourth dose of MTX. Prior single‐institution studies showed conflicting results comparing the outcomes of patients who received three versus four doses of MTX, but to our knowledge, the effect of concomitant antithymocyte globulin (ATG) has not been reported. Charts of patients who underwent MUD HSCT between 2009 and 2023 were reviewed. Patients received rabbit ATG (Thymoglobulin), given at 0.5 mg/kg on day −3, 2 mg/kg on day −2, and 2.5 mg/kg on day −1. MTX is given at 15 mg/m2 on day +1 and 10 mg/m2 on days +3, +6, and +11. Severe mucositis was the most common indication for day +11 MTX omission (82%). We identified 292 patients (116 in 3 dose cohort and 176 in 4 dose cohort). Median follow‐up was 23 months (range 1–151). Patients in the 4 doses cohort were more frequently male (68% vs. 50%, p

Plant-parasitic nematodes constrain global food security. During parasitism, they secrete effectors into the host plant from two types of pharyngeal gland cells. These effectors elicit profound changes in host biology to suppress immunity and establish a unique feeding organ from which the nematode draws nutrition. Despite the importance of effectors in nematode parasitism, there has been no comprehensive identification and characterisation of the effector repertoire of any plant-parasitic nematode. To address this, we advance techniques for gland cell isolation and transcriptional analysis to define a stringent annotation of putative effectors for the cyst nematode Heterodera schachtii at three key life-stages. We define 717 effector gene loci: 269 "known" high-confidence homologs of plant-parasitic nematode effectors, and 448 "novel" effectors with high gland cell expression. In doing so we define the most comprehensive "effectorome" of a plant-parasitic nematode to date. Using this effector definition, we provide the first systems-level understanding of the origin, deployment and evolution of a plant-parasitic nematode effectorome. The robust identification of the effector repertoire of a plant-parasitic nematode will underpin our understanding of nematode pathology, and hence, inform strategies for crop protection.

Abstract Most patients with advanced ovarian cancer (AOC) ultimately relapse after platinum-based chemotherapy. Combining bevacizumab, olaparib, and durvalumab likely drives synergistic activity. This open-label phase 2 study (NCT04015739) aimed to assess activity and safety of this triple combination in female patients with relapsed high-grade AOC following prior platinum-based therapy. Patients were treated with olaparib (300 mg orally, twice daily), the bevacizumab biosimilar FKB238 (15 mg/kg intravenously, once-every-3-weeks), and durvalumab (1.12 g intravenously, once-every-3-weeks) in nine French centers. The primary endpoint was the non-progression rate at 3 months for platinum-resistant relapse or 6 months for platinum-sensitive relapse per RECIST 1.1 and irRECIST. Secondary endpoints were CA-125 decline with CA-125 ELIMination rate constant K (KELIM-B) per CA-125 longitudinal kinetics over 100 days, progression free survival and overall survival, tumor response, and safety. Non-progression rates were 69.8% (90%CI 55.9%-80.0%) at 3 months for platinum-resistant relapse patients (N = 41), meeting the prespecified endpoint, and 43.8% (90%CI 29.0%-57.4%) at 6 months for platinum-sensitive relapse (N = 33), not meeting the prespecified endpoint. Median progression-free survival was 4.1 months (95%CI 3.5–5.9) and 4.9 months (95%CI 2.9–7.0) respectively. Favorable KELIM-B was associated with better survival. No toxic deaths or major safety signals were observed. Here we show that further investigation of this triple combination may be considered in AOC patients with platinum-resistant relapse.

Objective The aim of this study was to determine the effectiveness of a mechanical thrombectomy device in treating iliofemoral deep vein thrombosis (DVT) without thrombolysis and factors associated with post-thrombectomy occlusion.

Tree establishment following severe or stand-replacing disturbance is critical for achieving U.S. climate change mitigation goals and for maintaining the co-benefits of intact forest ecosystems. In many contexts, natural post-fire tree regeneration is sufficient to maintain forest cover and associated ecosystem services, but increasingly the pattern and scale of disturbance exceeds ecological thresholds and active reforestation may be warranted. Our capacity to plant trees, however, is not keeping pace with reforestation needs. This shortfall is uniquely apparent in the western U.S., where wildfire size and severity have increased in recent decades and long-term divestment in the reforestation supply chain has limited our ability to respond to existing needs. Here we present an analysis of key facets of both the supply and demand side of reforestation in the western U.S. and address six questions: (1) What is the current backlog of potential reforestation needs driven by high-severity wildfire?; (2) How will increasing wildfire activity through the end of the century affect potential reforestation needs?; (3) What is our capacity to meet current and future reforestation needs?; (4) How can we scale the reforestation supply chain to meet current and future demands?; (5) What approaches to reforestation can promote forest resilience to climate change and wildfire?; and (6) Where are opportunities emerging from recent policy initiatives, innovative public-private partnerships, and natural capital markets for scaling reforestation? Between 1984 and 2000, annual tree planting capacity met post-fire needs but cumulatively over the last two decades (2000 to 2021) it has fallen short of fire-driven needs by an estimated 1.5 million ha (ca. 3.8 million ac). We anticipate this gap will increase 2 to 3 fold by 2050. Scaling up reforestation efforts to close this gap will require increased investment across all facets of the reforestation supply chain, public-private partnerships, and novel approaches to reforestation that increase the resilience of western forests to drought and wildfire. We highlight emerging opportunities from recent policy initiatives and conservation finance for expanding reforestation efforts.

Primary gastric Burkitt’s lymphoma is an aggressive non-Hodgkin’s lymphoma that has been rarely reported in the literature. The majority of primary gastric lymphomas are diffuse large B-cell lymphomas and mucosa-associated lymphoid tissue (MALT) lymphomas. Patients with primary gastric Burkitt’s lymphoma can present with abdominal pain, hematemesis, melena, perforation, and obstruction. Diagnosis is made with a combination of clinical, radiological, and pathological findings. Treatment data are limited due to the limited cases reported. We present a case of a 47-year-old female who presented with diffuse abdominal pain, melena, and coffee-ground emesis that was diagnosed with primary gastric Burkitt’s lymphoma following biopsies taken from a gastric ulcerated mass found on upper endoscopy.

Short-rotation crop (SRC) systems with woody species have been planted in Costa Rica. However, information about different tree species and spacing is limited. The objective of the present study was to examine biomass production and the physical, energy, and chemical properties of feedstock of four tropical tree species (Cordia alliodora, Dipteryx panamensis, Gmelina arborea, and Tectona grandis) in 34-month-old plants planted at four spacings (0.5x1.0 m, 1.0x1.0 m, 1.0x2.0 m, and 2.0x2.0 m). The highest mortality rate (50%) was found in G. arborea; however, diameter, height, basal area, and biomass production in G. arborea plantations were higher than T. grandis, C. alliodora, and D. panamensis. Spacing effects on diameter, height, basal area, and biomass production were observed in 10-month-olds. Wide spacing presented the highest values in diameter and height, but the highest biomass production was found in the narrow spacing. Also, biomass distribution was different in D. panamensis in relation to other species. Specify gravity, density, and moisture content of biomass showed high variation between species and spacing, but the energy and chemical properties of biomass showed few differences. These results suggest that these four species were uniform in terms of their energy and chemical properties, regardless of the spacing used. Finally, three species (G. arborea, C. alliodora, and T. grandis) presented important potential for use in SRC systems. G. arborea was the species with the highest production but a high mortality rate.

Abstract Combination chemotherapy is crucial for successfully treating cancer. However, the enormous number of possible drug combinations means discovering safe and effective combinations remains a significant challenge. To improve this process, we conduct large-scale targeted CRISPR knockout screens in drug-treated cells, creating a genetic map of druggable genes that sensitize cells to commonly used chemotherapeutics. We prioritize neuroblastoma, the most common extracranial pediatric solid tumor, where ~50% of high-risk patients do not survive. Our screen examines all druggable gene knockouts in 18 cell lines (10 neuroblastoma, 8 others) treated with 8 widely used drugs, resulting in 94,320 unique combination-cell line perturbations, which is comparable to the largest existing drug combination screens. Using dense drug-drug rescreening, we find that the top CRISPR-nominated drug combinations are more synergistic than standard-of-care combinations, suggesting existing combinations could be improved. As proof of principle, we discover that inhibition of PRKDC, a component of the non-homologous end-joining pathway, sensitizes high-risk neuroblastoma cells to the standard-of-care drug doxorubicin in vitro and in vivo using patient-derived xenograft (PDX) models. Our findings provide a valuable resource and demonstrate the feasibility of using targeted CRISPR knockout to discover combinations with common chemotherapeutics, a methodology with application across all cancers.

Summary: Background: Although immunomodulators have established benefit against the new coronavirus disease (COVID-19) in general, it is uncertain whether such agents improve outcomes without increasing the risk of secondary infections in the specific subgroup of previously immunocompromised patients. We assessed the effect of immunomodulators on outcomes of immunocompromised patients hospitalized for COVID-19. Methods: The protocol was prospectively registered with PROSPERO (CRD42022335397). MEDLINE, Cochrane Central Register of Controlled Trials and references of relevant articles were searched up to 01-06-2022. Authors of potentially eligible randomized controlled trials were contacted to provide data on immunocompromised patients randomized to immunomodulators vs control (i.e., placebo or standard-of-care). Findings: Eleven randomized controlled trials involving 397 immunocompromised patients hospitalized for COVID-19 were included. Ten trials had low risk of bias. There was no difference between immunocompromised patients randomized to immunomodulators vs control regarding mortality [30/182 (16.5%) vs 41/215 (19.1%); RR 0.93, 95% CI 0.61–1.41; p = 0.74], secondary infections (RR 1.00, 95% CI 0.64–1.58; p = 0.99) and change in World Health Organization ordinal scale from baseline to day 15 (weighed mean difference 0.27, 95% CI -0.09–0.63; p = 0.15). In subgroup analyses including only patients with hematologic malignancy, only trials with low risk of bias, only trials administering IL-6 inhibitors, or only trials administering immunosuppressants, there was no difference between comparators regarding mortality. Interpretation: Immunomodulators, compared to control, were not associated with harmful or beneficial outcomes, including mortality, secondary infections, and change in ordinal scale, when administered to immunocompromised patients hospitalized for COVID-19. Funding: Hellenic Foundation for Research and Innovation.

Implication Statement Assessment of clinical teachers is a requirement by family medicine residency programs in Canada. This facilitates feedback to teachers and ensures the curriculum is delivered in an efficient and safe way. To protect resident confidentiality, preceptors often receive their teaching evaluations months to years later. Teachers have requested shorter feedback loops, greater numbers, and more frequent assessments to improve their skills. The preceptor field note (PFN) is a tool that allows learners to evaluate teachers during a single encounter providing more frequent and immediate feedback. This study documents teachers’ and residents’ initial impressions of the first iteration of the PFN.

Coronary atherosclerosis remains a leading cause of morbidity and mortality worldwide. The underlying pathophysiology includes a complex interplay of endothelial dysfunction, lipid accumulation and inflammatory pathways. Multiple structural and inflammatory features of the atherosclerotic lesions have become targets to identify high-risk lesions. Various intracoronary imaging devices have been developed to assess the morphological, biocompositional and molecular profile of the intracoronary atheromata. These techniques guide interventional and therapeutical management and allow the identification and stratification of atherosclerotic lesions. We sought to provide an overview of the inflammatory pathobiology of atherosclerosis, distinct high-risk plaque features and the ability to visualize this process with contemporary intracoronary imaging techniques.

Service-learning integrates community service with academic study. Students apply skills and knowledge in practical situations and reflect on their experiences. Our 3000-level service-learning college course, Leadership Development in Agricultural Sciences, involved student-led development and execution of a one-day event, “AgCamp,” held on a university campus for high school students. The objective of this study was to evaluate if an intervention (i.e., a service-learning project) changed undergraduate students’ perceptions of their ability to collaborate, ability to lead, and overall perceptions of the usefulness of service-learning. An electronic mixed methods questionnaire-based survey was developed, tested for validity and reliability, and distributed to college students enrolled in Leadership Development in Agricultural Sciences as a pre- and post-test at the beginning and end of two semesters. Data were analyzed in SPSS 26.0 using measures of central tendency and paired sample t-tests. Undergraduate students’ (n = 74) had positive perceptions of service-learning entering the semester, all measures of which improved as a result of their experiences in the course. In comparison with traditional courses, students felt service-learning courses have more societal benefits and should be increasingly offered. Participating in the service-learning project significantly increased students’ comfort working with people from different cultures or backgrounds and empowered them in different ways, including with decision-making. Ultimately, our data indicate that students enjoyed service-learning and received soft skill development through the course. We recommend service-learning be increasingly integrated into post-secondary curriculum.

Background: Standard views in two-dimensional echocardiography are well established but the qualities of acquired images are highly dependent on operator skills and are assessed subjectively. This study was aimed at providing an objective assessment pipeline for echocardiogram image quality by defining a new set of domain-specific quality indicators. Consequently, image quality assessment can thus be automated to enhance clinical measurements, interpretation, and real-time optimization. Methods: We developed deep neural networks for the automated assessment of echocardiographic frames that were randomly sampled from 11,262 adult patients. The private echocardiography dataset consists of 33,784 frames, previously acquired between 2010 and 2020. Unlike non-medical images where full-reference metrics can be applied for image quality, echocardiogram's data are highly heterogeneous and requires blind-reference (IQA) metrics. Therefore, deep learning approaches were used to extract the spatiotemporal features and the image's quality indicators were evaluated against the mean absolute error. Our quality indicators encapsulate both anatomical and pathological elements to provide multivariate assessment scores for anatomical visibility, clarity, depth-gain and foreshortedness. Results: The model performance accuracy yielded 94.4%, 96.8%, 96.2%, 97.4% for anatomical visibility, clarity, depth-gain and foreshortedness, respectively. The mean model error of 0.375±0.0052 with computational speed of 2.52 ms per frame (real-time performance) was achieved. Conclusion: The novel approach offers new insight to the objective assessment of transthoracic echocardiogram image quality and clinical quantification in A4C and PLAX views. It also lays stronger foundations for the operator's guidance system which can leverage the learning curve for the acquisition of optimum quality images during the transthoracic examination.