Despite their role in host nutrition, the anaerobic gut fungal (AGF) component of the herbivorous gut microbiome remains poorly characterized. Here, to examine global patterns and determinants of AGF diversity, we generate and analyze an amplicon dataset from 661 fecal samples from 34 mammalian species, 9 families, and 6 continents. We identify 56 novel genera, greatly expanding AGF diversity beyond current estimates (31 genera and candidate genera). Community structure analysis indicates that host phylogenetic affiliation, not domestication status and biogeography, shapes the community rather than. Fungal-host associations are stronger and more specific in hindgut fermenters than in foregut fermenters. Transcriptomics-enabled phylogenomic and molecular clock analyses of 52 strains from 14 genera indicate that most genera with preferences for hindgut hosts evolved earlier (44-58 Mya) than those with preferences for foregut hosts (22-32 Mya). Our results greatly expand the documented scope of AGF diversity and provide an ecologically and evolutionary-grounded model to explain the observed patterns of AGF diversity in extant animal hosts.

The statement that fully-grown porcine oocytes (oocytes from follicles with diameter from 3 to 6 mm) are transcriptionally quiescent is not as strongly supported as it was before. Currently, we know that there is a difference between the transcription profile of germinal vesicle (GV) and metaphase II (MII) oocytes. The goal of our study was to compare the transcription profile of GV, germinal vesicle breakdown (GVBD), metaphase I (MI), and MII oocytes matured in the chemically defined medium FLI. Oocytes were sequenced, and the results were subsequently validated using quantitative reverse transcription polymerase chain reaction (RT-qPCR). We detected multiple differentially transcribed mRNAs, of which many were upregulated. Among them we found mRNAs necessary for protein production, mitochondrial functions and cytoplasmic maturation. Collectively, these data support the hypothesis that transcription activity in fully-grown porcine oocytes is necessary for key processes during their successful maturation in vitro in a chemically defined maturation medium.

The use of mutation analysis of homologous recombination repair (HRR) genes to estimate PARP-inhibition response may miss a larger proportion of responding patients. Here, we provide preclinical models for castration-resistant prostate cancer (CRPC) that can be used to functionally predict HRR defects. In vitro, CRPC LNCaP sublines revealed an HRR defect and enhanced sensitivity to olaparib and cisplatin due to impaired RAD51 expression and recruitment. Ex vivo-induced castration-resistant tumor slice cultures or tumor slice cultures derived directly from CRPC patients showed increased olaparib- or cisplatin-associated enhancement of residual radiation-induced γH2AX/53BP1 foci. We established patient-derived tumor organoids (PDOs) from CRPC patients. These PDOs are morphologically similar to their primary tumors and genetically clustered with prostate cancer but not with normal prostate or other tumor entities. Using these PDOs, we functionally confirmed the enhanced sensitivity of CRPC patients to olaparib and cisplatin. Moreover, olaparib but not cisplatin significantly decreased the migration rate in CRPC cells. Collectively, we present robust patient-derived preclinical models for CRPC that recapitulate the features of their primary tumors and enable individualized drug screening, allowing translation of treatment sensitivities into tailored clinical therapy recommendations.

OBJECTIVE: Anterior lumbar interbody fusion (ALIF) is a surgical treatment that requires a close operative plane to the great vessels, which increases the risk of perioperative complications. To our knowledge, no previous study has investigated the American Society of Anesthesiologists (ASA) Physical Status Classification System as a predictive factor for unfavorable perioperative outcomes in ALIF procedures. We aimed to analyze the ASA score as a predictive factor of intraoperative and postoperative outcomes in patients undergoing ALIFs.

METHODS: A retrospective chart review was completed at each center to identify a consecutive set of patients who underwent an ALIF. Univariate and multivariate analyses between patients with preoperative ASA scores of ≤2 and >2 were performed to identify predictive factors that may contribute to adverse intraoperative and early postoperative outcomes.

RESULTS: Among 210 patients identified, 59 (28.1%) had an ASA score >2 and 151 (71.9%) had an ASA score ≤2. On multivariate analysis, an ASA score >2 was predictive of increased 90-day reoperations (P = 0.02), estimated blood loss (EBL) (P = 0.02), and operative time (P = 0.02). Previous lumbar surgery was predictive of increased length of stay (P = 0.005), EBL (P < 0.001), 90-day readmission (P = 0.02), and operative time (P < 0.001). Posterior supplemental fixation was predictive of increased length of stay (P = 0.04). Increased number of operative levels was predictive of increased EBL (P < 0.001) and operative time (P < 0.001). Perioperative anticoagulation use was predictive of increased EBL (P < 0.001) CONCLUSIONS: Increased ASA scores were associated with unfavorable outcomes after ALIF and also can be used as a predictive tool for the risk of reoperations.

During the coronavirus disease 2019 (COVID-19) pandemic, the urgency for updated evidence to inform public health and clinical care placed systematic literature reviews (SLRs) at the cornerstone of research. We aimed to summarize evidence on prognostic factors for COVID-19 outcomes through published SLRs and to critically assess quality elements in the findings' interpretation. An umbrella review was conducted via electronic databases from January 2020 to April 2022. All SLRs (and meta-analyses) in English were considered. Data screening and extraction were conducted by two independent reviewers. AMSTAR 2 tool was used to assess SLR quality. The study was registered with PROSPERO (CRD4202232576). Out of 4,564 publications, 171 SLRs were included of which 3 were umbrella reviews. Our primary analysis included 35 SLRs published in 2022, which incorporated studies since the beginning of the pandemic. Consistent findings showed that, for adults, older age, obesity, heart disease, diabetes, and cancer were more strongly predictive of risk of hospitalization, intensive care unit admission, and mortality due to COVID-19. Male sex was associated with higher risk of short-term adverse outcomes, but female sex was associated with higher risk of long COVID. For children, socioeconomic determinants that may unravel COVID-19 disparities were rarely reported. This review highlights key prognostic factors of COVID-19, which can help clinicians and health officers identify high-risk groups for optimal care. Findings can also help optimize confounding adjustment and patient phenotyping in comparative effectiveness research. A living SLR approach may facilitate dissemination of new findings. This paper is endorsed by the International Society for Pharmacoepidemiology.

The induction of an effective immune response is critical for the success of mRNA-based therapeutics. Here, we developed a nanoadjuvant system compromised of Quil-A and DOTAP (dioleoyl 3 trimethylammonium propane), hence named QTAP, for the efficient delivery of mRNA vaccine constructs into cells. Electron microscopy indicated that the complexation of mRNA with QTAP forms nanoparticles with an average size of 75 nm and which have  90% encapsulation efficiency. The incorporation of pseudouridine-modified mRNA resulted in higher transfection efficiency and protein translation with low cytotoxicity than unmodified mRNA. When QTAP-mRNA or QTAP alone transfected macrophages, pro-inflammatory pathways (e.g., NLRP3, NF-kb, and MyD88) were upregulated, an indication of macrophage activation. In C57Bl/6 mice, QTAP nanovaccines encoding Ag85B and Hsp70 transcripts (QTAP-85B+H70) were able to elicit robust IgG antibody and IFN- ɣ, TNF-α, IL-2, and IL-17 cytokines responses. Following aerosol challenge with a clinical isolate of M. avium ss. hominissuis (M.ah), a significant reduction of mycobacterial counts was observed in lungs and spleens of only immunized animals at both 4- and 8-weeks post-challenge. As expected, reduced levels of M. ah were associated with diminished histological lesions and robust cell-mediated immunity. Interestingly, polyfunctional T-cells expressing IFN- ɣ, IL-2, and TNF- α were detected at 8 but not 4 weeks post-challenge. Overall, our analysis indicated that QTAP is a highly efficient transfection agent and could improve the immunogenicity of mRNA vaccines against pulmonary M. ah, an infection of significant public health importance, especially to the elderly and to those who are immune compromised.

Antibiotic resistance is a global health concern. Strains of pathogenic microorganisms that have developed resistance to multiple antibiotics, such as {MRSA}, are extremely difficult to treat, and alternative methods for tackling pathogenic microorganisms are in demand. One potential target for new therapeutics is inhibition of quorum sensing: how microorganisms communicate and form biofilms in a density-dependent manner. Inhibiting this system via ‘quorum quenching’ ({QQ}) is a promising route to new pharmaceuticals and for controlling biofilm formation and growth. Quorum sensing also provides interesting possibilities in synthetic biology for producing novel products, biosensors, bioactive molecules, and so on. This book covers the biology of quorum sensing and quenching, and potential sources of {QQ} enzymes and other inhibitors, as well as an overview of their mechanism and potential biotech applications. The book also covers the potential for new drug development from {QQ}, covering a range of related topics including protein engineering, imaging and computational studies, and integrated systems. This book is an ideal companion to researchers in chemical biology and medicinal chemistry, particularly those interested in biofilm formation, quorum sensing, novel antimicrobial development, synthetic biology and enzymology.

OBJECTIVE: The aim of this paper was to evaluate the changes in radiographic spinopelvic parameters in a large cohort of patients undergoing the prone transpsoas approach to the lumbar spine.

METHODS: A multicenter retrospective observational cohort study was performed for all patients who underwent lateral lumber interbody fusion via the single-position prone transpsoas (PTP) approach. Spinopelvic parameters from preoperative and first upright postoperative radiographs were collected, including lumbar lordosis (LL), pelvic incidence (PI), and pelvic tilt (PT). Functional indices (visual analog scale score), and patient-reported outcomes (Oswestry Disability Index) were also recorded from pre- and postoperative appointments.

RESULTS: Of the 363 patients who successfully underwent the procedure, LL after fusion was 50.0° compared with 45.6° preoperatively (p < 0.001). The pelvic incidence-lumbar lordosis mismatch (PI-LL) was 10.5° preoperatively versus 2.9° postoperatively (p < 0.001). PT did not significantly change (0.2° ± 10.7°, p > 0.05).

CONCLUSIONS: The PTP approach allows significant gain in lordotic augmentation, which was associated with good functional results at follow-up.

The emergence of probiotics as an alternative and adjunct to antibiotic treatment for microbiological disturbances of the female genitourinary system requires innovative delivery platforms for vaginal applications. This study developed a new, rapid-dissolving form using electrospun polyethylene oxide (PEO) fibers for delivery of antibiotic metronidazole or probiotic Lactobacillus acidophilus, and performed evaluation in vitro and in vivo. Fibers did not generate overt pathophysiology or encourage Gardnerella growth in a mouse vaginal colonization model, inducing no alterations in vaginal mucosa at 24 hr post-administration. PEO-fibers incorporating metronidazole (100 µg MET/mg polymer) effectively prevented and treated Gardnerella infections (∼3- and 2.5-log reduction, respectively, 24 hr post treatment) when administered vaginally. Incorporation of live Lactobacillus acidophilus (10 CFU/mL) demonstrated viable probiotic delivery in vitro by PEO and polyvinyl alcohol (PVA) fibers to inhibit Gardnerella (10 CFU/mL) in bacterial co-cultures (9.9- and 7.0-log reduction, respectively, 24 hr post-inoculation), and in the presence of vaginal epithelial cells (6.9- and 8.0-log reduction, respectively, 16 hr post-inoculation). Administration of Lactobacillus acidophilus in PEO-fibers achieved vaginal colonization in mice similar to colonization observed with free Lactobacillus. acidophilus. These experiments provide proof-of-concept for rapid-dissolving electrospun fibers as a successful platform for intra-vaginal antibiotic or probiotic delivery.

BACKGROUND: Artificial intelligence (AI) has attracted much attention because of its enormous potential in healthcare, but uptake has been slow. There are substantial barriers that challenge health technology assessment (HTA) professionals to use AI-generated evidence for decision-making from large real-world databases (e.g., based on claims data). As part of the European Commission-funded HTx H2020 (Next Generation Health Technology Assessment) project, we aimed to put forward recommendations to support healthcare decision-makers in integrating AI into the HTA processes. The barriers, addressed by the paper, are particularly focusing on Central and Eastern European (CEE) countries, where the implementation of HTA and access to health databases lag behind Western European countries.

METHODS: We constructed a survey to rank the barriers to using AI for HTA purposes, completed by respondents from CEE jurisdictions with expertise in HTA. Using the results, two members of the HTx consortium from CEE developed recommendations on the most critical barriers. Then these recommendations were discussed in a workshop by a wider group of experts, including HTA and reimbursement decision-makers from both CEE countries and Western European countries, and summarized in a consensus report.

RESULTS: Recommendations have been developed to address the top 15 barriers in areas of (1) human factor-related barriers, focusing on educating HTA doers and users, establishing collaborations and best practice sharing; (2) regulatory and policy-related barriers, proposing increasing awareness and political commitment and improving the management of sensitive information for AI use; (3) data-related barriers, suggesting enhancing standardization and collaboration with data networks, managing missing and unstructured data, using analytical and statistical approaches to address bias, using quality assessment tools and quality standards, improving reporting, and developing better conditions for the use of data; and (4) technological barriers, suggesting sustainable development of AI infrastructure.

CONCLUSION: In the field of HTA, the great potential of AI to support evidence generation and evaluation has not yet been sufficiently explored and realized. Raising awareness of the intended and unintended consequences of AI-based methods and encouraging political commitment from policymakers is necessary to upgrade the regulatory and infrastructural environment and knowledge base required to integrate AI into HTA-based decision-making processes better.

With the advent of multiplex fluorescence in situ hybridization (FISH) and in situ RNA sequencing technologies, spatial transcriptomics analysis is advancing rapidly, providing spatial location and gene expression information about cells in tissue sections at single cell resolution. Cell type classification of these spatially-resolved cells can be inferred by matching the spatial transcriptomics data to reference atlases derived from single cell RNA-sequencing (scRNA-seq) in which cell types are defined by differences in their gene expression profiles. However, robust cell type matching of the spatially-resolved cells to reference scRNA-seq atlases is challenging due to the intrinsic differences in resolution between the spatial and scRNA-seq data. In this study, we systematically evaluated six computational algorithms for cell type matching across four image-based spatial transcriptomics experimental protocols (MERFISH, smFISH, BaristaSeq, and ExSeq) conducted on the same mouse primary visual cortex (VISp) brain region. We find that many cells are assigned as the same type by multiple cell type matching algorithms and are present in spatial patterns previously reported from scRNA-seq studies in VISp. Furthermore, by combining the results of individual matching strategies into consensus cell type assignments, we see even greater alignment with biological expectations. We present two ensemble meta-analysis strategies used in this study and share the consensus cell type matching results in the Cytosplore Viewer ( https://viewer.cytosplore.org ) for interactive visualization and data exploration. The consensus matching can also guide spatial data analysis using SSAM, allowing segmentation-free cell type assignment.

PURPOSE: To determine risk factors increasing susceptibility to early complications (intraoperative and postoperative within 6 weeks) associated with surgery to correct thoracic and lumbar spinal deformity.

METHODS: We systematically searched the PubMed and EMBASE databases for studies published between January 1990 and September 2021. Observational studies evaluating predictors of early complications of thoracic and lumbar spinal deformity surgery were included. Pooled odds ratio (OR) or standardized mean difference (SMD) with 95% confidence intervals (CI) was calculated via the random effects model.

RESULTS: Fifty-two studies representing 102,432 patients met the inclusion criteria. Statistically significant patient-related risk factors for early complications included neurological comorbidity (OR = 3.45, 95% CI 1.83-6.50), non-ambulatory status (OR = 3.37, 95% CI 1.96-5.77), kidney disease (OR = 2.80, 95% CI 1.80-4.36), American Society of Anesthesiologists score > 2 (OR = 2.23, 95% CI 1.76-2.84), previous spine surgery (OR = 1.98, 95% CI 1.41-2.77), pulmonary comorbidity (OR = 1.94, 95% CI 1.21-3.09), osteoporosis (OR = 1.60, 95% CI 1.17-2.20), cardiovascular diseases (OR = 1.46, 95% CI 1.20-1.78), hypertension (OR = 1.37, 95% CI 1.23-1.52), diabetes mellitus (OR = 1.84, 95% CI 1.30-2.60), preoperative Cobb angle (SMD = 0.43, 95% CI 0.29, 0.57), number of comorbidities (SMD = 0.41, 95% CI 0.12, 0.70), and preoperative lumbar lordotic angle (SMD = - 0.20, 95% CI - 0.35, - 0.06). Statistically significant procedure-related factors were fusion extending to the sacrum or pelvis (OR = 2.53, 95% CI 1.53-4.16), use of osteotomy (OR = 1.60, 95% CI 1.12-2.29), longer operation duration (SMD = 0.72, 95% CI 0.05, 1.40), estimated blood loss (SMD = 0.46, 95% CI 0.07, 0.85), and number of levels fused (SMD = 0.37, 95% CI 0.03, 0.70).

CONCLUSION: These data may contribute to development of a systematic approach aimed at improving quality-of-life and reducing complications in high-risk patients.

OBJECTIVE: To determine COVID-19 vaccine-related adverse events (AEs) in the seven-day post-vaccination period in patients with SLE vs autoimmune rheumatic diseases (AIRDs), non-rheumatic autoimmune diseases (nrAIDs), and healthy controls (HC).

METHODS: Data were captured through the COVID-19 Vaccination in Autoimmune Diseases (COVAD) questionnaire (March-December 2021). Multivariable regression models accounted for age, gender, ethnicity, vaccine type and background treatment.

RESULTS: Among 9462 complete respondents, 583 (6.2%) were SLE patients (mean age: 40.1 years; 94.5% females; 40.5% Asian; 42.9% Pfizer-recipients). Minor AEs were reported by 83.0% of SLE patients, major by 2.6%, hospitalization by 0.2%. AE and hospitalization frequencies were similar between patients with active and inactive SLE. Rashes were more frequent in SLE patients vs HC (OR; 95% CI: 1.2; 1.0, 1.5), chills less frequent in SLE vs AIRDs (0.6; 0.4, 0.8) and nrAIDs (0.5; 0.3, 0.8), and fatigue less frequent in SLE vs nrAIDs (0.6; 0.4, 0.9). Pfizer-recipients reported higher overall AE (2.2; 1.1, 4.2) and injection site pain (2.9; 1.6, 5.0) frequencies than recipients of other vaccines, Oxford/AstraZeneca-recipients more body ache, fever, chills (OR: 2.5, 3.0), Moderna-recipients more body ache, fever, chills, rashes (OR: 2.6, 4.3). Hospitalization frequencies were similar across vaccine types. AE frequencies were similar across treatment groups, although chills were less frequent in antimalarial users vs non-users (0.5; 0.3, 0.9).

CONCLUSION: While COVID-19 vaccination-related AEs were reported by four-fifths of SLE patients, those were mostly minor and comparable to AEs reported by healthy individuals, providing reassurance regarding COVID-19 vaccination safety in SLE.

Duchenne muscular dystrophy is caused by mutations in the DMD gene, leading to lack of dystrophin. Chronic muscle damage eventually leads to histological alterations in skeletal muscles. The identification of genes and cell types driving tissue remodeling is a key step to developing effective therapies. Here we use spatial transcriptomics in two Duchenne muscular dystrophy mouse models differing in disease severity to identify gene expression signatures underlying skeletal muscle pathology and to directly link gene expression to muscle histology. We perform deconvolution analysis to identify cell types contributing to histological alterations. We show increased expression of specific genes in areas of muscle regeneration (Myl4, Sparc, Hspg2), fibrosis (Vim, Fn1, Thbs4) and calcification (Bgn, Ctsk, Spp1). These findings are confirmed by smFISH. Finally, we use differentiation dynamic analysis in the D2-mdx muscle to identify muscle fibers in the present state that are predicted to become affected in the future state.