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Clostridioides difficile is a bacterial pathogen responsible for significant morbidity and mortality across the globe. Current therapies based on broad-spectrum antibiotics have some clinical success, but approximately 30% of patients have relapses, presumably due to the continued perturbation to the gut microbiota. Here, we show that phages can be engineered with type I CRISPR-Cas systems and modified to reduce lysogeny and to enable the specific and efficient targeting and killing of C. difficile in vitro and in vivo. Additional genetic engineering to disrupt phage modulation of toxin expression by lysogeny or other mechanisms would be required to advance a CRISPR-enhanced phage antimicrobial for C. difficile toward clinical application. These findings provide evidence into how phage can be combined with CRISPR-based targeting to develop novel therapies and modulate microbiomes associated with health and disease. Clostridioides difficile is an important nosocomial pathogen that causes approximately 500,000 cases of C. difficile infection (CDI) and 29,000 deaths annually in the United States. Antibiotic use is a major risk factor for CDI because broad-spectrum antimicrobials disrupt the indigenous gut microbiota, decreasing colonization resistance against C. difficile . Vancomycin is the standard of care for the treatment of CDI, likely contributing to the high recurrence rates due to the continued disruption of the gut microbiota. Thus, there is an urgent need for the development of novel therapeutics that can prevent and treat CDI and precisely target the pathogen without disrupting the gut microbiota. Here, we show that the endogenous type I-B CRISPR-Cas system in C. difficile can be repurposed as an antimicrobial agent by the expression of a self-targeting CRISPR that redirects endogenous CRISPR-Cas3 activity against the bacterial chromosome. We demonstrate that a recombinant bacteriophage expressing bacterial genome-targeting CRISPR RNAs is significantly more effective than its wild-type parent bacteriophage at killing C. difficile both in vitro and in a mouse model of CDI. We also report that conversion of the phage from temperate to obligately lytic is feasible and contributes to the therapeutic suitability of intrinsic C. difficile phages, despite the specific challenges encountered in the disease phenotypes of phage-treated animals. Our findings suggest that phage-delivered programmable CRISPR therapeutics have the potential to leverage the specificity and apparent safety of phage therapies and improve their potency and reliability for eradicating specific bacterial species within complex communities, offering a novel mechanism to treat pathogenic and/or multidrug-resistant organisms. IMPORTANCE Clostridioides difficile is a bacterial pathogen responsible for significant morbidity and mortality across the globe. Current therapies based on broad-spectrum antibiotics have some clinical success, but approximately 30% of patients have relapses, presumably due to the continued perturbation to the gut microbiota. Here, we show that phages can be engineered with type I CRISPR-Cas systems and modified to reduce lysogeny and to enable the specific and efficient targeting and killing of C. difficile in vitro and in vivo. Additional genetic engineering to disrupt phage modulation of toxin expression by lysogeny or other mechanisms would be required to advance a CRISPR-enhanced phage antimicrobial for C. difficile toward clinical application. These findings provide evidence into how phage can be combined with CRISPR-based targeting to develop novel therapies and modulate microbiomes associated with health and disease.

By following the common definition of forward-dynamics simulations, i.e. predicting movement based on (neural) muscle activity, this work describes, for the first time, a forward-dynamics simulation framework of a musculoskeletal system, in which all components are represented as continuous, three-dimensional, volumetric objects. Within this framework, the mechanical behaviour of the entire muscle–tendon complex is modelled as a nonlinear hyperelastic material undergoing finite deformations. The feasibility and the full potential of the proposed forward-dynamics simulation framework is demonstrated on a two-muscle, three-dimensional, continuum-mechanical model of the upper limb. The musculoskeletal model consists of three bones, i.e. humerus, ulna, and radius, an one-degree-of-freedom elbow joint, and an antagonistic muscle pair, i.e. the biceps and triceps brachii, and takes into consideration the contact between the skeletal muscles and the humerus. Numerical studies have shown that the proposed upper limb model is capable of predicting realistic moment arms and muscle forces for the entire range of activation and motion. Within the limitations of the model, the presented simulations provide, for the first time, insights into existing contact forces and their influence on the muscle fibre stretch. Based on the presented simulations, the overall change in fibre stretch is typically less than 3%, despite the fact that the contact forces reach up to 71% of the exerted muscle force. Movement-predicting simulations are achieved by minimising a nonlinear moment equilibrium equation. Based on the forward-dynamics simulation approach, an iterative solution procedures for position-driven (inverse dynamics) and force-driven scenarios have been proposed accordingly. Applying these methodologies to time-dependent scenarios demonstrates that the proposed methods can be linked to state-of-the-art control algorithms predicting time-dependent muscle activation levels based on principles of forward dynamics.

Lower limb prosthesis users often struggle to navigate uneven terrain or ambulate in low light conditions where it can be challenging to rely on visual cues for balance and walking. Sensory feedback about foot-floor interactions may allow users to reduce reliance on secondary sensory cues and improve confidence and speed when navigating difficult terrain. Our group has developed a Sensory Neuroprosthesis (SNP) to restore sensation to people with lower limb amputation by pairing electrical stimulation of nerves in the residual limb applied implanted neurotechnology with pressure sensors in the insole of a standard prosthesis. Stimulation applied to the nerves evoked sensations perceived as originating on the missing leg and foot. This qualitative case study reports on the experiences of a 68-year-old with a unilateral trans-tibial amputation who autonomously used the SNP at home for 31 weeks. Interview data collected throughout the study period was analyzed using a grounded theory approach with constant comparative methods to understand his experience with this novel technology and its impacts on his daily life. A conceptual model was developed that explained the experience of integrating SNP-provided sensory feedback into his body and motor plans. The model described the requirements of integration, which were a combination of a low level of mental focus and low stimulation levels. While higher levels of stimulation and focus could result in distinct sensory percepts and various phantom limb experiences, optimal integration was associated with SNP-evoked sensation that was not readily perceivable. Successful sensorimotor integration of the SNP resulted in improvements to locomotion, a return to a more normal state, an enhancement of perceived prosthesis utility, and a positive outlook on the experience. These outcomes emerged over the course of the nearly 8 month study, suggesting that findings from long-term home studies of SNPs may differ from those of short-term in-laboratory tests. Our findings on the experience of sensorimotor integration of the SNP have implications for the optimal training of SNP users and the future deployment of clinical SNP systems for long-term home use.

Hill-type muscle models are commonly used in biomechanical simulations to predict passive and active muscle forces. Here, a model is presented which consists of four elements: a contractile element with force–length and force–velocity relations for concentric and eccentric contractions, a parallel elastic element, a series elastic element, and a serial damping element. With this, it combines previously published effects relevant for muscular contraction, i.e. serial damping and eccentric force–velocity relation. The model is exemplarily applied to arm movements. The more realistic representation of the eccentric force–velocity relation results in human-like elbow-joint flexion. The model is provided as ready to use Matlab ® and Simulink ® code.

This study contrasted the use of responsiveness indices at the group level vs. individual patient level. We followed a cohort of 211 patients (50% male; mean age 47.5 years; SD 14) with musculoskeletal upper extremity problems for a total of 3 months. Outcome measures included the Disabilities of the Arm, Shoulder, and Hand (DASH) questionnaire, Shoulder Pain and Disability Index (SPADI), Patient-Rated Wrist Evaluation (PRWE), and the Medical Outcomes Study 12-Item Short-Form Health Survey (SF-12). We calculated confidence intervals on various group-level responsiveness statistics based on effect size and correlation with global change. The proportion of patients exceeding the minimum detectable change (or reliable change proportion) and minimum important difference (MID proportion) were included as indices applicable to the individual patient. For the DASH, effect size ranged from 1.06 to 1.67 for various patient subgroups, and the reliable change and MID proportions indicated that 50%–70% of individuals exhibited change based on individual change scores. Only the SRM and reliable change proportion indicated differences among the outcome measures used in this study. The reliable change and MID proportions have an intuitive interpretation and facilitate quantitative responsiveness comparisons among outcome measures based on individual patient criteria.

Nitrogen-vacancy (NV) centers in diamond are appealing nanoscale quantum sensors for temperature, strain, electric fields, and, most notably, magnetic fields. However, the cryogenic temperatures required for low-noise single-shot readout that have enabled the most sensitive NV magnetometry reported to date are impractical for key applications, e.g., biological sensing. Overcoming the noisy readout at room temperature has until now demanded the repeated collection of fluorescent photons, which increases the time cost of the procedure, thus reducing its sensitivity. Here, we show how machine learning can process the noisy readout of a single NV center at room temperature, requiring on average only one photon per algorithm step, to sense magnetic-field strength with a precision comparable to those reported for cryogenic experiments. Analyzing large datasets from NV centers in bulk diamond, we report absolute sensitivities of60nTs1/2including initialization, readout, and computational overheads. We show that dephasing times can be simultaneously estimated and that time-dependent fields can be dynamically tracked at room temperature. Our results dramatically increase the practicality of early-term single-spin sensors.

Purpose: To investigate pan-ethnic SMN1 copy-number and sequence variation by hybridization-based target enrichment coupled with massively parallel sequencing or next-generation sequencing (NGS). Methods: NGS reads aligned to SMN1 and SMN2 exon 7 were quantified to determine the total combined copy number of SMN1 and SMN2 . The ratio of SMN1 to SMN2 was calculated based on a single-nucleotide difference that distinguishes the two genes. SMN1 copy-number results were compared between the NGS and quantitative polymerase chain reaction and/or multiplex ligation-dependent probe amplification. The NGS data set was also queried for the g.27134T>G single-nucleotide polymorphism (SNP) and other SMN1 sequence pathogenic variants. Results: The sensitivity of the test to detect spinal muscular atrophy (SMA) carriers with one copy of SMN1 was 100% (95% confidence interval (CI): 95.9–100%; n = 90) and specificity was 99.6% (95% CI: 99.4–99.7%; n = 6,648). Detection of the g.27134T>G SNP by NGS was 100% concordant with an restriction fragment-length polymorphism method ( n = 493). Ten single-nucleotide variants in SMN1 were detectable by NGS and confirmed by gene-specific amplicon-based sequencing. This comprehensive approach yielded SMA carrier detection rates of 90.3–95.0% in five ethnic groups studied. Conclusion: We have developed a novel, comprehensive SMN1 copy-number and sequence variant analysis method by NGS that demonstrated improved SMA carrier detection rates across the entire population examined. Genet Med advance online publication 19 January 2017

Single NV centers in diamond coupled by hyperfine interaction (hfi) to neighboring 13C nuclear spins are now widely used in emerging quantum technologies as elements of quantum memory adjusted to a nitrogen-vacancy (NV) center electron spin qubit. For nuclear spins with low flip-flop rate, single shot readout was demonstrated under ambient conditions. Here we report on a systematic search for such stable NV−13C systems using density functional theory to simulate the hfi and spatial characteristics of all possible NV−13C complexes in the H-terminated cluster C510[NV]-H252 hosting the NV center. Along with the expected stable 'NV-axial−13C' systems wherein the 13C nuclear spin is located on the NV axis, we found for the first time new families of positions for the 13C nuclear spin exhibiting negligible hfi-induced flipping rates due to near-symmetric local spin density distribution. Spatially, these positions are located in the diamond bilayer passing through the vacancy of the NV center and being perpendicular to the NV axis. Analysis of available publications showed that, apparently, some of the predicted non-axial near-stable NV−13C systems have already been observed experimentally. A special experiment performed on one of these systems confirmed the prediction made.

Background: The mitochondrial DNA (mtDNA) depletion syndromes (MDDSs) are autosomal recessive disorders characterized by a reduction in cellular mtDNA content. Mutations in at least 9 genes [POLG, polymerase (DNA directed), gamma; DGUOK, deoxyguanosine kinase; TK2, thymidine kinase, mitochondrial; TYMP, thymidine phosphorylase; MPV17, MpV17 mitochondrial inner membrane protein; SUCLA2, succinate-CoA ligase, ADP-forming, beta subunit; SUCLG1, succinate-CoA ligase, alpha subunit; RRM2B, RRM2B, ribonucleotide reductase M2 B (TP53 inducible); and C10orf2, chromosome 10 open reading frame 2 (also known as TWINKLE)] have been reported to cause mtDNA depletion. In the clinical setting, a simple method to quantify mtDNA depletion would be useful before undertaking gene sequence analysis. Methods: Real-time quantitative PCR (qPCR) was used to measure the mtDNA content in blood, muscle, and liver samples and in skin fibroblast cultures from individuals suspected of mitochondrial disorders, with or without deleterious mutations in genes responsible for MDDS. Results: The mtDNA content was quantified in 776 tissue samples (blood, n = 341; muscle, n = 325; liver, n = 63; skin fibroblasts, n = 47) from control individuals. mtDNA content increased with age in muscle tissue, decreased with age in blood samples, and appeared to be unaffected by age in liver samples. In 165 samples (blood, n = 122; muscle, n = 21; liver, n = 15; skin fibroblasts, n = 7) from patients with molecularly proven MDDSs, severe mtDNA depletion was detected in liver and muscle tissue with high specificity and sensitivity. Blood samples were specific but not sensitive for detecting mtDNA depletion, and skin fibroblasts were not valuable for evaluating mtDNA depletion. Mutations in the POLG, RRM2B, and MPV17 genes were prospectively identified in 1 blood, 1 liver, and 3 muscle samples. Conclusions: Muscle and liver tissues, but not blood or skin fibroblasts, are potentially useful for rapid screening for mtDNA depletion with real-time qPCR.

Determining the internal dynamics of the human spine’s biological structure is one essential step that allows enhanced understanding of spinal degeneration processes. The unavailability of internal load figures in other methods highlights the importance of the forward dynamics approach as the most powerful approach to examine the internal degeneration of spinal structures. Consequently, a forward dynamics full-body model of the human body with a detailed lumbar spine is introduced. The aim was to determine the internal dynamics and the contribution of different spinal structures to loading. The multi-body model consists of the lower extremities, two feet, shanks and thighs, the pelvis, five lumbar vertebrae, and a lumped upper body including the head and both arms. All segments are modelled as rigid bodies. 202 muscles (legs, back, abdomen) are included as Hill-type elements. 58 nonlinear force elements are included to represent all spinal ligaments. The lumbar intervertebral discs were modelled nonlinearly. As results, internal kinematics, muscle forces, and internal loads for each biological structure are presented. A comparison between the nonlinear (new, enhanced modelling approach) and linear (standard modelling approach, bushing) modelling approaches of the intervertebral disc is presented. The model is available to all researchers as ready-to-use C/C++ code within our in-house multi-body simulation code demoa with all relevant binaries included.