Increasing the accuracy of exchange parameters reporting on slow dynamics by performing CEST experiments with 'high' B1 fields.

Over the last decade chemical exchange saturation transfer (CEST) NMR methods have emerged as powerful tools to characterize biomolecular conformational dynamics occurring between a visible major state and 'invisible' minor states. The ability of the CEST experiment to detect these minor states, and provide precise exchange parameters, hinges on using appropriate B1 field strengths during the saturation period. Typically, a pair of B1 fields with ω1 (=2πB1) values around the exchange rate kex are chosen. Here we show that the transverse relaxation rate of the minor state resonance (R2,B) also plays a crucial role in determining the B1 fields that lead to the most informative datasets. Using [Formula: see text]  ≥ kex, to guide the choice of B1, instead of kex, leads to data wherefrom substantially more accurate exchange parameters can be derived. The need for higher B1 fields, guided by K, is demonstrated by studying the conformational exchange in two mutants of the 71 residue FF domain with kex âˆ¼ 11 s-1 and âˆ¼ 72 s-1, respectively. In both cases analysis of CEST datasets recorded using B1 field values guided by kex lead to imprecise exchange parameters, whereas using B1 values guided by K resulted in precise site-specific exchange parameters. The conclusions presented here will be valuable while using CEST to study slow processes at sites with large intrinsic relaxation rates, including carbonyl sites in small to medium sized proteins, amide 15N sites in large proteins and when the minor state dips are broadened due to exchange among the minor states.

Solution-state methyl NMR spectroscopy of large non-deuterated proteins enabled by deep neural networks.

Methyl-TROSY nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for characterising large biomolecules in solution. However, preparing samples for these experiments is demanding and entails deuteration, limiting its use. Here we demonstrate that NMR spectra recorded on protonated, uniformly 13C labelled samples can be processed using deep neural networks to yield spectra that are of similar quality to typical deuterated methyl-TROSY spectra, potentially providing information for proteins that cannot be produced in bacterial systems. We validate the methodology experimentally on three proteins with molecular weights in the range 42-360 kDa. We further demonstrate the applicability of our methodology to 3D NOESY spectra of Escherichia coli Malate Synthase G (81 kDa), where observed NOE cross-peaks are in good agreement with the available structure. The method represents an advance in the field of using deep learning to analyse complex magnetic resonance data and could have an impact on the study of large biomolecules in years to come.

Permanent lingual nerve injury after dental procedures: a retrospective study of 228 patients.

Lingual nerve injury (LNI) is a rare, serious complication and previous studies include limited numbers of cases. The aim of this retrospective study was to report the neurosensory outcomes for a large patient cohort with permanent LNI and correlate the mechanism of injury (surgical vs non-surgical) to neurosensory characteristics. Demographics, procedural parameters, mandibular third molar (M3) position, surgeon type, neurosensory test results, and symptoms were recorded for 228 patients and analysed. The majority were female (67.1%). Overall, 59.6% of LNIs were caused by M3 removal and 36.4% by local anaesthesia. Complete loss occurred more frequently in surgical LNIs (P = 0.013). The presence of pain did not differ significantly, however the burning type of pain was significantly more frequent in non-surgical LNIs (P = 0.008) along with altered gustation (P = 0.025). The most common M3 position related to LNI was distoangular (40.4%), class III (63.2%), level A (58.1%) (Winter/Pell and Gregory classifications). The majority of patients undergoing M3 removal were >24 years. A total of 71.7% showed no sign of recovery and 5.5% reported further impairment in their condition. Overall, nine patients underwent microsurgical repair. This study presents neurosensory characteristics potentially decisive for timely referral of operable LNIs.

The impact of gastroesophageal reflux disease and its treatment on interstitial lung disease outcomes.

BACKGROUND: To determine the relationship between gastroesophageal reflux disease (GORD) and its treatment and interstitial lung disease in patients with systemic sclerosis (SSc). METHODS: SSc patients from the Australian Scleroderma Cohort Study (ASCS) were included. GORD was defined as self-reported GORD symptoms, therapy with a proton pump inhibitor (PPI) or histamine 2 receptor antagonist (H2RA) and/or the presence of reflux oesophagitis diagnosed endoscopically. The impact of GORD and its treatment on ILD features (including severity and time to ILD development) and survival was evaluated. RESULTS: GORD was a common manifestation affecting 1539/1632 (94%) of SSc patients. GORD affected 450/469 (96%) of those with SSc-ILD cohort. In SSc-ILD, there was no relationship between the presence of GORD or its treatment and time to ILD development or ILD severity. However, GORD treatment was associated with improved survival in those with ILD (p = 0.002). Combination therapy with both a PPI and a H2RA was associated with a greater survival benefit than single agent therapy with PPI alone (HR 0.3 vs 0.5 p < 0.050 respectively). CONCLUSION: GORD is a common SSc disease manifestation. While the presence or treatment of GORD does not influence the development or severity of ILD, aggressive GORD treatment, in particular with a combination of PPI and H2RA, is associated with improved survival in those with SSc-ILD.

Biological Upcycling of Plastics Waste.

Plastic wastes accumulate in the environment, impacting wildlife and human health and representing a significant pool of inexpensive waste carbon that could form feedstock for the sustainable production of commodity chemicals, monomers, and specialty chemicals. Current mechanical recycling technologies are not economically attractive due to the lower-quality plastics that are produced in each iteration. Thus, the development of a plastics economy requires a solution that can deconstruct plastics and generate value from the deconstruction products. Biological systems can provide such value by allowing for the processing of mixed plastics waste streams via enzymatic specificity and using engineered metabolic pathways to produce upcycling targets. We focus on the use of biological systems for waste plastics deconstruction and upcycling. We highlight documented and predicted mechanisms through which plastics are biologically deconstructed and assimilated and provide examples of upcycled products from biological systems. Additionally, we detail current challenges in the field, including the discovery and development of microorganisms and enzymes for deconstructing non-polyethylene terephthalate plastics, the selection of appropriate target molecules to incentivize development of a plastic bioeconomy, and the selection of microbial chassis for the valorization of deconstruction products.

Deep generative modeling of the human proteome reveals over a hundred novel genes involved in rare genetic disorders.

Identifying causal mutations accelerates genetic disease diagnosis, and therapeutic development. Missense variants present a bottleneck in genetic diagnoses as their effects are less straightforward than truncations or nonsense mutations. While computational prediction methods are increasingly successful at prediction for variants in known disease genes, they do not generalize well to other genes as the scores are not calibrated across the proteome1-6. To address this, we developed a deep generative model, popEVE, that combines evolutionary information with population sequence data7 and achieves state-of-the-art performance at ranking variants by severity to distinguish patients with severe developmental disorders8 from potentially healthy individuals9. popEVE identifies 442 genes in patients this developmental disorder cohort, including evidence of 123 novel genetic disorders, many without the need for gene-level enrichment and without overestimating the prevalence of pathogenic variants in the population. A majority of these variants are close to interacting partners in 3D complexes. Preliminary analyses on child exomes indicate that popEVE can identify candidate variants without the need for inheritance labels. By placing variants on a unified scale, our model offers a comprehensive perspective on the distribution of fitness effects across the entire proteome and the broader human population. popEVE provides compelling evidence for genetic diagnoses even in exceptionally rare single-patient disorders where conventional techniques relying on repeated observations may not be applicable.

Picosecond Dynamics of a Small Molecule in Its Bound State with an Intrinsically Disordered Protein.

Intrinsically disordered proteins (IDPs) are highly dynamic biomolecules that rapidly interconvert among many structural conformations. These dynamic biomolecules are involved in cancers, neurodegeneration, cardiovascular illnesses, and viral infections. Despite their enormous therapeutic potential, IDPs have generally been considered undruggable because of their lack of classical long-lived binding pockets for small molecules. Currently, only a few instances are known where small molecules have been observed to interact with IDPs, and this situation is further exacerbated by the limited sensitivity of experimental techniques to detect such binding events. Here, using experimental nuclear magnetic resonance (NMR) spectroscopy 19F transverse spin-relaxation measurements, we discovered that a small molecule, 5-fluoroindole, interacts with the disordered domains of non-structural protein 5A from hepatitis C virus with a Kd of 260 ± 110 µM. Our analysis also allowed us to determine the rotational correlation times (τc) for the free and bound states of 5-fluoroindole. In the free state, we observed a rotational correlation time of 27.0 ± 1.3 ps, whereas in the bound state, τc only increased to 46 ± 10 ps. Our findings imply that it is possible for small molecules to engage with IDPs in exceptionally dynamic ways, in sharp contrast to the rigid binding modes typically exhibited when small molecules bind to well-defined binding pockets within structured proteins.

Prioritization, Incentives, and Resource Use for Sustainable Dentistry: The EU PRUDENT Project.

KNOWLEDGE TRANSFER STATEMENT: The EU PRUDENT project aims to enhance the financing of oral health systems through novel evidence and implementation of better financing solutions together with citizens, patients, providers, and policy makers. The multicountry nature of the project offers unique windows of opportunity for rapid learning and improving within and across various contexts. PRUDENT is anticipated to strengthen capacities for better oral care financing in the EU and worldwide.

Deep generative modeling of the human proteome reveals over a hundred novel genes involved in rare genetic disorders.

Identifying causal mutations accelerates genetic disease diagnosis, and therapeutic development. Missense variants present a bottleneck in genetic diagnoses as their effects are less straightforward than truncations or nonsense mutations. While computational prediction methods are increasingly successful at prediction for variants in known disease genes, they do not generalize well to other genes as the scores are not calibrated across the proteome. To address this, we developed a deep generative model, popEVE, that combines evolutionary information with population sequence data and achieves state-of-the-art performance at ranking variants by severity to distinguish patients with severe developmental disorders from potentially healthy individuals. popEVE identifies 442 genes in a cohort of developmental disorder cases, including evidence of 119 novel genetic disorders without the need for gene-level enrichment and without overestimating the prevalence of pathogenic variants in the population. By placing variants on a unified scale, our model offers a comprehensive perspective on the distribution of fitness effects across the entire proteome and the broader human population. popEVE provides compelling evidence for genetic diagnoses even in exceptionally rare single-patient disorders where conventional techniques relying on repeated observations may not be applicable. Interactive web viewer and downloads available at pop.evemodel.org.

A ring shear device to simulate cryosphere processes.

We have developed a new cryogenic ring shear device at the University of Wisconsin-Madison to simulate cryosphere processes, with an emphasis on the physics of glacier slip. The device spins a ring of ice (inner diameter of 20 cm, outer diameter of 60 cm, height of ∼20-30 cm) at the pressure melting point over a rotationally fixed bed. The ice ring is spun at a prescribed velocity (range of ∼0.01-1000 m a-1) while the resistance to slip is measured. A ram at the base of the device applies a vertical load to the sample chamber to simulate the overburden pressure (range ∼5-915 kPa) felt at a glacier's base. The sample chamber is constructed with transparent acrylic walls, allowing subglacial processes to be observed directly by a series of cameras. The entire device is housed in a large walk-in freezer. In the freezer, the sample chamber is submerged in a tub of temperature-controlled fluid that precisely regulates heat flux into the sample chamber, replicating in situ conditions and allowing for prolonged experiments that last weeks to months. This device can be used to study several of the most unconstrained physical processes that regulate glacier movement and, in doing so, greatly improve predictions of glacier contributions to sea-level rise.

Biomolecular NMR spectroscopy in the era of artificial intelligence.

Biomolecular nuclear magnetic resonance (NMR) spectroscopy and artificial intelligence (AI) have a burgeoning synergy. Deep learning-based structural predictors have forever changed structural biology, yet these tools currently face limitations in accurately characterizing protein dynamics, allostery, and conformational heterogeneity. We begin by highlighting the unique abilities of biomolecular NMR spectroscopy to complement AI-based structural predictions toward addressing these knowledge gaps. We then highlight the direct integration of deep learning approaches into biomolecular NMR methods. AI-based tools can dramatically improve the acquisition and analysis of NMR spectra, enhancing the accuracy and reliability of NMR measurements, thus streamlining experimental processes. Additionally, deep learning enables the development of novel types of NMR experiments that were previously unattainable, expanding the scope and potential of biomolecular NMR spectroscopy. Ultimately, a combination of AI and NMR promises to further revolutionize structural biology on several levels, advance our understanding of complex biomolecular systems, and accelerate drug discovery efforts.

Intrinsic structural dynamics dictate enzymatic activity and inhibition.

Enzymes are known to sample various conformations, many of which are critical for their biological function. However, structural characterizations of enzymes predominantly focus on the most populated conformation. As a result, single-point mutations often produce structures that are similar or essentially identical to those of the wild-type enzyme despite large changes in enzymatic activity. Here, we show for mutants of a histone deacetylase enzyme (HDAC8) that reduced enzymatic activities, reduced inhibitor affinities, and reduced residence times are all captured by the rate constants between intrinsically sampled conformations that, in turn, can be obtained independently by solution NMR spectroscopy. Thus, for the HDAC8 enzyme, the dynamic sampling of conformations dictates both enzymatic activity and inhibitor potency. Our analysis also dissects the functional role of the conformations sampled, where specific conformations distinct from those in available structures are responsible for substrate and inhibitor binding, catalysis, and product dissociation. Precise structures alone often do not adequately explain the effect of missense mutations on enzymatic activity and drug potency. Our findings not only assign functional roles to several conformational states of HDAC8 but they also underscore the paramount role of dynamics, which will have general implications for characterizing missense mutations and designing inhibitors.

Confined placental mosaicism: placental size and function evaluated on magnetic resonance imaging.

OBJECTIVES: Evidence regarding placental function in pregnancies complicated by confined placental mosaicism (CPM) is conflicting. We aimed to compare placental function between CPM and non-CPM pregnancies prenatally and at birth. A secondary objective was to evaluate the relationship between placental function and chromosomal subtype of CPM. METHODS: This was a retrospective study of pregnancies with CPM and control pregnancies delivered at a tertiary hospital in Denmark between 2014 and 2017. Placental volume and placental transverse relaxation time (T2*) were estimated on magnetic resonance imaging (MRI), fetal weight and uterine artery pulsatility index (UtA-PI) were estimated on ultrasound and fetoplacental ratio was assessed on MRI and at birth. These estimates of placental function were adjusted for gestational age and compared between groups using the Wilcoxon rank-sum test. Within the group of CPM pregnancies, measures of placental function were compared between those at high risk (chromosome numbers 2, 3, 7, 13 and 16) and those at low risk (chromosome numbers 5, 18 and 45X). RESULTS: A total of 90 pregnancies were included, of which 12 had CPM and 78 were controls. MRI and ultrasound examinations were performed at a median gestational age of 32.6 weeks (interquartile range, 24.7-35.3 weeks). On MRI assessment, CPM placentae were characterized by a lower placental T2* Z-score (P = 0.004), a lower fetoplacental ratio (P = 0.03) and a higher UtA-PI Z-score (P = 0.03), compared with non-CPM placentae. At birth, the fetoplacental ratio was significantly lower (P = 0.02) and placental weight Z-score was higher (P = 0.01) in CPM pregnancies compared with non-CPM pregnancies. High-risk CPM pregnancies showed a reduced placental T2* Z-score (P = 0.003), lower birth-weight Z-score (P = 0.041), earlier gestational age at delivery (P = 0.019) and higher UtA-PI Z-score (P = 0.028) compared with low-risk CPM pregnancies. Low-risk CPM pregnancies did not differ in any of these parameters from non-CPM pregnancies. CONCLUSIONS: CPM pregnancies are characterized by an enlarged and dysfunctional placenta. Placental function was highly related to the chromosomal type of CPM; placental dysfunction was seen predominantly in high-risk CPM pregnancies in which chromosomes 2, 3, 7, 13 or 16 were involved. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Placental volume, thickness and transverse relaxation time (T2*) estimated by magnetic resonance imaging in relation to small for gestational age at birth.

INTRODUCTION: Placental magnetic resonance imaging (MRI) may be a valuable tool in the prediction of small for gestational age (SGA) at birth. MRI provides reliable estimates of placental volume and thickness. In addition, placental transverse relaxation time (T2*) may be directly related to placental function. This study aimed to explore and compare the predictive performance of three placental MRI parameters - volume, thickness and T2* - in relation to SGA at birth. METHODS: A mixed cohort of 85 pregnancies was retrieved from the placental MRI database at the study hospital. MRI was performed in a 1.5 T system at gestational weeks 15-41. In normal birthweight (BW) pregnancies [BW > -22 % of expected for gestational age (GA)], the correlation between each of the MRI parameters and GA was investigated by linear regression. The prediction of SGA was investigated by logistic regression analysis adjusted for GA at MRI. RESULTS: In normal BW pregnancies, a significant linear correlation was found between GA and each of the MRI parameters. Univariate analysis demonstrated that placental volume [odds ratio (OR) 0.97, p = 0.001] and placental T2* (OR 0.79, p = 0.003), but not placental thickness (OR 0.92, p = 0.862) were significant predictors of SGA. A multi-variate model including all three MRI parameters found that placental T2* was the only independent predictor of SGA (OR 0.81, p = 0.04). CONCLUSION: Among the MRI parameters investigated in this study, placental T2* was the only independent predictor of SGA in a multi-variate model. This finding underlines the strong position of T2*-weighted placental MRI in the prediction of SGA.

Less is more: A simple methyl-TROSY based pulse scheme offers improved sensitivity in applications to high molecular weight complexes.

The HMQC pulse sequence and variants thereof have been exploited in studies of high molecular weight protein complexes, taking advantage of the fact that fast and slow relaxing magnetization components are sequestered along two distinct magnetization transfer pathways. Despite the simplicity of the HMQC scheme an even shorter version can be designed, based on elimination of the terminal refocusing period, as a further means of increasing signal. Here we present such an experiment, and show that significant sensitivity gains, in some cases by factors of two or more, are realized in studies of proteins varying in molecular masses from 100 kDa to 1 MDa.

Implementation of robot-assisted groin hernia repair diminishes the prospects of young surgeons' training: a nationwide register-based cohort study.

PURPOSE: Robot-assisted groin hernia repair is becoming more popular in recent years but may remove operations from surgical trainees. We aimed to investigate the educational level of the surgeons who performed robot-assisted groin hernia repair and the rate of supervision and compare this to open and laparoscopic groin hernia repair. METHODS: This register-based study was reported according to the RECORD statement and used linked data from the Danish Hernia Database and the Danish Patient Safety Authority's Online Register. We included surgeons that performed robot-assisted, laparoscopic, and/or open groin hernia repairs performed between January 1, 2015, and June 15, 2021 in Denmark. RESULTS: A total of 916 surgeons performing 43,856 groin hernia repairs were included in this study. Surgical specialists performed 98% of the robot-assisted groin hernia repairs, 89% of the laparoscopic repairs (p < 0.0001), and 54% of the Lichtenstein repairs (p < 0.0001). Only 5% of the robot-assisted groin hernia repairs were supervised compared with 11% of the laparoscopic repairs (p < 0.0001) and 28% of the open repairs (p < 0.0001). CONCLUSION: Almost all groin hernia repairs performed with the robot-assisted technique were performed by surgeons specialized in general surgery. The proportions of surgeons specialized in surgery were higher for robot-assisted operations compared with laparoscopic or open groin hernia surgery. Thus, our data suggest a lack of involvement of surgeons in training, and this diminishes the educational potential in the pool of groin hernia operations by the use of robot-assisted repairs.

Optimizing frequency sampling in CEST experiments.

For the past decade chemical exchange saturation transfer (CEST) experiments have been successfully applied to study exchange processes in biomolecules involving sparsely populated, transiently formed conformers. Initial implementations focused on extensive sampling of the CEST frequency domain, requiring significant measurement times. Here we show that the lengthy sampling schemes often used are not optimal and that reduced frequency sampling schedules can be developed without a priori knowledge of the exchange parameters, that only depend on the chosen B1 field, and, to a lesser extent, on the intrinsic transverse relaxation rates of ground state spins. The reduced sampling approach described here can be used synergistically with other methods for reducing measurement times such as those that excite multiple frequencies in the CEST dimension simultaneously, or make use of non-uniform sampling of indirectly detected time domains, to further decrease measurement times. The proposed approach is validated by analysis of simulated and experimental datasets.

The psychological subtype of intimate partner violence and its effect on mental health: a systematic review with meta-analyses.

PURPOSE: The present study examines the association between psychological violence and posttraumatic stress disorder (PTSD), depression, and anxiety, while comparing the specific subtypes of psychological violence and simultaneously focusing on methodological shortcomings. METHOD: A systematic review and random-effects meta-analyses were applied on the three main outcomes: PTSD, depression, and anxiety. Four electronic databases were searched (PsycINFO, PubMed, EMBASE, and Web of Science), and a total of 194 studies were included (k = 149 for meta-analyses). GRADEpro was used to evaluate the certainty of the evidence from the meta-analyses. RESULTS: Psychological violence had strong associations with the three main outcomes, with the strongest association for PTSD in both female and male victims. Coercive control was particularly associated with PTSD for female victims, while emotional/verbal and dominance/isolation had the strongest association with depression. Although the identified studies were characterized by gender bias, psychological violence appear to affect male mental health too. DISCUSSION: Findings from the meta-analyses support the notion that psychological violence is a traumatic experience, which is strongly association with PTSD and other common mental health problems linked to trauma. GRADEpro rated the certainty of evince to be low, and thus, our confidence in the estimated effect is limited. Gender bias, the applied terminology, and other methodological shortcomings are discussed. Despite the substantial amount of research on this topic, more research is needed before we can draw any final conclusions on the effect of psychological violence on mental health.

Oestrus status does not alter breeding suitability assessments regarding medial patellar luxation in female small breed dogs: A blinded multi-observer study.

Study aims were to evaluate if medial patellar luxation clinical grades changed with oestrus status, and to determine interobserver agreement for different classification methods for grading patellar luxation. Intact female dogs were recruited for grading by 3 independent observers on 2 occasions (pro-oestrus/oestrus and dioestrus/anoestrus) using a published grading system. Observers were blinded to oestrus status. Oestrus status was confirmed by vaginal cytology. Observer agreement was determined using Fleiss' multirater kappa on the original grading scores, simplification to the Norwegian Kennel Club system, and further simplification to a binary suitable/not-suitable for breeding system. The exact McNemar's test was used to assess the effect of oestrus on classification. Of 70 dogs recruited, 53 underwent paired observations. Interobserver agreement was considered moderate to very good for the study sub-groups, with overall kappa values of 0.68 (95% CI 0.63-0.72), 0.79 (0.73-0.84) and 0.92 (0.85-0.99), and percentage agreements of 65%, 81% and 94%, for the original, simplified and binary classifications. Oestrus status did not have a significant effect on classification of breeding suitability. Clinicians and owners should not be concerned about the timing of patellar luxation grading in relation to oestrus. Experienced observers show good or very good agreement using the Norwegian Kennel Club and binary categorisations.

Circadian rhythm of markers of bone turnover in patients with chronic kidney disease.

Patients with chronic kidney disease (CKD) have a high risk of bone fractures. A circadian rhythmicity in turnover and mineralization of bone appears to be of importance for bone health. In CKD disturbances in the circadian rhythm of various functions has been demonstrated and indeed the circadian rhythm in the mineral metabolism is disturbed. The aim of the present study was to compare the circadian rhythm of bone turnover markers in ten patients with CKD to ten healthy controls. Bone turnover markers (C-terminal telopeptide of type I collagen, tartrate-resistant acid phosphatase 5b, N-terminal propeptide of type I procollagen, bone alkaline phosphatase and osteocalcin) were measured every third hour for 24 h. All bone turnover markers displayed a significant circadian rhythm in both groups and there were no significant differences in the rhythmicity between the two groups (no group*time interaction). As expected, due to the reduced renal clearance, the overall level of C-terminal telopeptide of type I collagen and osteocalcin was higher in CKD compared to the healthy controls. The present study suggests that disturbances in the circadian rhythm of bone turnover do not explain the metabolic bone disease and increased risk of fractures in CKD.