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Distal arthrogryposis type 5D (DA5D), a rare autosomal recessive disorder, is caused by mutations in ECEL1. We describe two consanguineous families (three patients) with novel ECEL1 gene mutations detected by next-generation sequencing (NGS). A 12-year-old boy (patient 1) presented with birth asphyxia, motor developmental delay, multiple joint contractures, pes planus, kyphoscoliosis, undescended testis, hypophonic speech with a nasal twang, asymmetric ptosis, facial weakness, absent abductor pollicis brevis, bifacial, and distal lower limb weakness. Muscle MRI revealed asymmetric fatty infiltration of tensor fascia lata, hamstring, lateral compartment of the leg, and gastrocnemius. In addition, 17-year-old monozygotic twins (patients 2 and 3) presented with motor development delay, white hairlock, hypertelorism, tented upper lip, bulbous nose, tongue furrowing, small low set ears, multiple contractures, pes cavus, prominent hyperextensibility at the knee, hypotonia of lower limbs, wasting and weakness of all limbs (distal > proximal), areflexia, and high steppage gait. One had perinatal insult, seizures, mild intellectual disability, unconjugated eye movements, and primary optic atrophy. In the twins, MRI revealed extensive fatty infiltration of the gluteus maximus, quadriceps, hamstrings, and anterior and posterior compartment of the leg. Electrophysiology showed prominent motor axonopathy. NGS revealed rare homozygous missense variants c.602T > C (p.Met201Thr) in patient 1 and c.83C > T (p.Ala28Val) in patients 2 and 3, both localized in exon 2 of ECEL1 gene. Our three cases expand the clinical, imaging, and molecular spectrum of the ECEL1-mutation-related DA5D.

BACKGROUND AND OBJECTIVES Muscle ultrasound (MUS) is an emerging noninvasive tool to identify fasciculations in amyotrophic lateral sclerosis (ALS). We assessed the utility of MUS in detecting fasciculations in suspected ALS patients. METHODS Thirty-three patients (25 men) with possible (n = 7), probable (n = 12), or definite ALS according to Awaji criteria were studied. Electromyography was done in biceps brachii, quadriceps, and thoracic paraspinal muscles and MUS in biceps, triceps, deltoid, abductor-digiti-minimi, quadriceps, hamstrings, tibialis anterior, thoracic paraspinal, and tongue muscles. RESULTS The age at onset and illness duration was 49.73 ± 12.7 years and 13.57 ± 9.7 months, respectively. Limb-onset = 24 patients (72.7%) and bulbar-onset = 9 (27.3%). Totally 561 muscles were examined by MUS. Fasciculations were detected in 84.3% of muscles, 98.4% with and 73% without clinical fasciculations (p

Cross-sectional area (CSA) is the most important parameter to study peripheral nerves by high-resolution ultrasonography. The aim was to acquire normative data of CSA of the main upper and lower limb nerves in the Indian population.CSA of nerves was determined in 100 healthy volunteers at 11 predetermined sites: median and ulnar at the wrist, mid-forearm, elbow; radial (spiral groove); tibial (popliteal fossa, medial malleolus); common peroneal (CPN, fibular head) and sural (lateral malleolus).The mean age of participants was 40.7 ± 13.0 years (range: 18-79). Fifty were40 years of age. The mean height, weight and BMI were 161.5 ± 8.3 centimeters (range: 145-179), 58.6 ± 10.1 kilograms (range: 32-90) and 22.4 ± 3.2 kilogram/square meter (range: 14.03-30.44), respectively. The median and ulnar nerve measurements were non-uniform throughout its course, and the CSA was largest at the elbow and ulnar groove, respectively. With advancing age, there was a significant difference for median and ulnar nerves at the wrist (medianIt is apt for every defined population to have its own set of normative data of CSA as it varies with ethnicity, age, and the built of individuals. We provide a valuable set of CSA data for nerves in the Indian population, which can be used for comparison while investigating peripheral nerve disorders.

This paper studies an RF MEMS Switch which consists on a thin bridge which is micromachined and suspended on a layer of dielectric. When a pull-in voltage is applied to the switch, the bridge will deform and settle on to the dielectric layer and thus the capacitance is increased. An imaginary force (contact force) is used here for the micromachined thin bridge to collapse on to the dielectric layer. 1mv of an input voltage is applied to measure the capacitance of the device, which is then increased to 5 V after 25 μs by using a step function having a rise time of 10 μs. The displacement of 2.5E-8 m is achieved and capacitance of 6.8pF is measured by applying 5 V of an input voltage. Nitinol which is shape memory alloy (SMA) is used to model the thin bridge and Silicon Nitride layer acts as a dielectric layer. Since the applied input voltage is greater than the required pull-in voltage, the switch comes in contact with the nitride layer. The complete simulation is carried out in COMSOL Multiphysics.

Purpose The purpose of this paper is to solve economic emission dispatch problem in connection of wind with hydro-thermal units. Design/methodology/approach The proposed hybrid methodology is the joined execution of both the modified salp swarm optimization algorithm (MSSA) with artificial intelligence technique aided with particle swarm optimization (PSO) technique. Findings The proposed approach is introduced to figure out the optimal power generated power from the thermal, wind farms and hydro units by minimizing the emission level and cost of generation simultaneously. The best compromise solution of the generation power outputs and related gas emission are subject to the equality and inequality constraints of the system. Here, MSSA is used to generate the optimal combination of thermal generator with the objective of minimum fuel and emission objective function. The proposed method also considers wind speed probability factor via PSO-artificial neural network (ANN) technique and hydro power generation at peak load demand condition to ensure economic utilization. Originality/value To validate the advantage of the proposed approach, six- and ten-units thermal systems are studied with fuel and emission cost. For minimizing the fuel and emission cost of the thermal system with the predicted wind speed factor, the proposed approach is used. The proposed approach is actualized in MATLAB/Simulink, and the results are examined with considering generation units and compared with various solution techniques. The comparison reveals the closeness of the proposed approach and proclaims its capability for handling multi-objective optimization problems of power systems.

Ardita vata presenting with palsy of one side of the face is akin to Bell's palsy or acute idiopathic lower motor neuron facial palsy. This is characterized by sudden-onset paralysis or weakness of the muscles to one side of the face controlled by the facial nerve. Bell's palsy is an idiopathic, presumed immune-mediated phenomenon, possibly with an infection as the inciting event. In contemporary science, administration of steroids is the treatment of choice for complete facial palsy. A 17-year-old boy diagnosed with Ardita vata due to chronic ear infection was treated with Karpasasthyadi taila Nasya and oral Ayurvedic medicines along with two sittings of the Panchakarma procedure. The total duration of the treatment was 4 months; however, significant results observed after 1 month of treatment shown almost complete recovery without any concurrent medications. The patient suffers from the same complaint 5 years ago in the right side of his face, and for that, he took 2 years of allopathic treatment and got complete relief. This case is evidence to demonstrate the effectiveness of Ayurveda treatment in case of Ardita vata (Bell's palsy) and as a proposition for further research on a greater number of patients.

Although protein-protein interactions (PPIs) have emerged as an attractive therapeutic target space, the identification of chemicals that effectively inhibit PPIs remains challenging. Here, we identified through library screening a chemical probe (compound 1) that can inhibit the tumor-promoting interaction between the oncogenic factor exon 2–depleted splice variant of aminoacyl–transfer RNA synthetase-interacting multifunctional protein 2 (AIMP2-DX2) and heat shock protein 70 (HSP70). We found that compound 1 binds to the N-terminal subdomain of glutathione S-transferase (GST-N) of AIMP2-DX2, causing a direct steric clash with HSP70 and an intramolecular interaction between the N-terminal flexible region and the GST-N of AIMP2-DX2, which induces masking of the HSP70 binding region during molecular dynamics and mutation studies. Compound 1 thus interferes with the AIMP2-DX2 and HSP70 interaction and suppresses the growth of cancer cells that express high levels of AIMP2-DX2 in vitro and in preliminary in vivo experiment. This work provides an example showing that allosteric conformational changes induced by chemicals can be a way to control pathologic PPIs. SIGNIFICANCE STATEMENT Compound 1 is a promising protein-protein interaction inhibitor between AIMP2-DX2 and HSP70 for cancer therapy by the mechanism with allosteric modulation as well as competitive binding. It seems to induce allosteric conformational change of AIMP2-DX2 proteins and direct binding clash between AIMP2-DX2 and HSP70. The compound reduced the level of AIMP2-DX2 in ubiquitin-dependent manner via suppression of binding between AIMP2-DX2 and HSP70 and suppressed the growth of cancer cells highly expressing AIMP2-DX2 in vitro and in preliminary in vivo experiment.

Background Cancer patients are at increased risk of death from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Cancer and its treatment affect many haematological and biochemical parameters, therefore we analysed these prior to and during coronavirus disease 2019 (COVID-19) and correlated them with outcome. Patients and methods Consecutive patients with cancer testing positive for SARS-CoV-2 in centres throughout the United Kingdom were identified and entered into a database following local governance approval. Clinical and longitudinal laboratory data were extracted from patient records. Data were analysed using Mann–Whitney U test, Fisher's exact test, Wilcoxon signed rank test, logistic regression, or linear regression for outcomes. Hierarchical clustering of heatmaps was performed using Ward's method. Results In total, 302 patients were included in three cohorts: Manchester (n = 67), Liverpool (n = 62), and UK (n = 173). In the entire cohort (N = 302), median age was 69 (range 19-93 years), including 163 males and 139 females; of these, 216 were diagnosed with a solid tumour and 86 with a haematological cancer. Preinfection lymphopaenia, neutropaenia and lactate dehydrogenase (LDH) were not associated with oxygen requirement (O2) or death. Lymphocyte count (P < 0.001), platelet count (P = 0.03), LDH (P < 0.0001) and albumin (P < 0.0001) significantly changed from preinfection to during infection. High rather than low neutrophils at day 0 (P = 0.007), higher maximal neutrophils during COVID-19 (P = 0.026) and higher neutrophil-to-lymphocyte ratio (NLR; P = 0.01) were associated with death. In multivariable analysis, age (P = 0.002), haematological cancer (P = 0.034), C-reactive protein (P = 0.004), NLR (P = 0.036) and albumin (P = 0.02) at day 0 were significant predictors of death. In the Manchester/Liverpool cohort 30 patients have restarted therapy following COVID-19, with no additional complications requiring readmission. Conclusion Preinfection biochemical/haematological parameters were not associated with worse outcome in cancer patients. Restarting treatment following COVID-19 was not associated with additional complications. Neutropaenia due to cancer/treatment is not associated with COVID-19 mortality. Cancer therapy, particularly in patients with solid tumours, need not be delayed or omitted due to concerns that treatment itself increases COVID-19 severity., Highlights • Pre-infection haematological/biochemical characteristics are not associated with COVID-19 severity. • Significant haematological/biochemical changes occur upon infection with heterogeneity in response observed. • High not low neutrophils were associated with oxygen requirement and COVID-19 mortality – GCSF should be used with caution. Age, haematological cancer, high neutrophil:lymphocyte ratio, CRP and low albumin were significant predictors of death in multivariable analysis. No significant complications requiring readmission were seen upon restart of cancer therapy following diagnosis of COVID-19.

Background: Patients with cancer are at increased risk of severe COVID-19, but have heterogeneous presentations and outcomes. Decision-making tools for hospital admission, severity prediction and increased monitoring for early intervention are critical. We sought to identify features of COVID-19 in cancer patients predicting severe disease and build a decision-support online tool; COVID-19 Risk in Oncology Evaluation Tool (CORONET). Methods: Patients with active cancer (stage I-IV) and laboratory confirmed COVID-19 presenting to hospitals worldwide were included. Discharge (within 24hrs), admission (≥24hrs inpatient), oxygen requirement (O2) and death were combined in a 0-3 point severity scale. Association of features with outcome were investigated using Lasso regression and Random Forest (RF) combined with SHapley Additive exPlanations (SHAP). RF was further validated in 4 cohorts, split by geography. The CORONET model was then examined in the entire cohort to build an online CORONET decision-support tool. Admission and severe disease thresholds were established through pragmatically defined cost functions. Findings: The dataset comprised 920 patients; median age 70 (range 5-99), 56% males, 44% females, 81% solid vs. 19% haematological cancers. In derivation, RF demonstrated superior performance over Lasso with lower mean squared error (0.801 vs. 0.807) and was selected for development. During validation, RF achieved mean AUROC 0.77, 0.80 and 0.75 for prediction of admission, O 2 and death, respectively. Using the entire cohort, CORONET cut-offs for admission and mortality of 1.0 and 2.3 were established. The CORONET decision support tool recommended admission for 95% of patients eventually requiring oxygen and 97% of those who died. SHAP explanations revealed National-Early-Warning-Score-2, C-reactive protein and albumin were the most important features contributing to COVID-19 severity prediction in patients with cancer at time of hospital presentation. Interpretation: CORONET, a decision-support tool validated in healthcare systems worldwide can aid admission decisions and predict COVID-19 severity in patients with cancer. Funding Information: R. Lee and T. Robinson and J. Weaver are supported by the National Institute for Health Research as Clinical Lecturers. T. Bhogal is supported by the National Institute for Health Research as an academic clinical fellow. U. Khan is an MRC Clinical Training Fellow based at the University of Liverpool supported by the North West England Medical Research Council Fellowship Scheme in Clinical Pharmacology and Therapeutics, which is funded by the Medical Research Council (Award Ref. MR/N025989/1). The Liverpool Experimental Cancer Medicine Centre for providing infrastructure support (Grant Reference: C18616/A25153) and The Clatterbridge Cancer charity (North West Cancer Research). C. Dive is funded by CRUK Core funding to Manchester Institute (C5757/A27412) and is supported by the CRUK Manchester Centre Award (C5759/A25254), and by the NIHR Manchester Biomedical Research Centre. C. Zhou is funded by the CRUK Manchester Centre Award (C5759/A25254), J. Stevenson and P. Fitzpatrick are funded by the CRUK Accelerator Award (29374). This research was funded in part, by the Wellcome Trust [205228/Z/16/Z]. LT is also supported by the National Institute for Health Research Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections (NIHR200907) at University of Liverpool in partnership with Public Health England (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford. LT is based at University of Liverpool. MS is supported by a grant from the Ministry of Science and Higher Education of the Russian Federation for the state support for the creation and development of World Class Research Centers "Digital biodesign and personalized healthcare” N.075-15-2020-926. Declaration of Interests: R Lee research funding (institution) BMS and speaker fees Astrazeneca. A. Croitoru Consulting or Advisory Role: Lilly, Merck, Roche, Bayer, Novartis, Ipsen, Research Funding me and my hospital: Gilead Sciences, Pfizer, Canfite, NanoCarrier, Bristol-Myers Squibb, Merck, Amgen, Servier, Five Prime Therapeutics, Travel Accommodations: Pfizer, Genekor, and oz, Merck, Pfizer, Servier, Roche. O. Michielin reports personal fees from Bristol-Myers Squibb, personal fees from MSD, personal fees from Novartis, personal fees from Roche, personal fees from Amgen, personal fees from NeraCare GmbH, outside the submitted work. E. Romano institutional research grants from Amgen, Astra Zeneca, Bristol-Myers Squibb. G. Pentheroudakis advisory board for Amgen, Astra Zeneca, Bristol-Myers Squibb, Lilly, Merck, MSD, Roche, Abbvie, institutional research grants from Amgen, Astra Zeneca, Boehringer Ingelheim, Bristol Myers Squibb, Debbio, Enorasis, Genekor, Ipsen, Janssen, Lilly, Merck, MSD, Pfizer, Roche, Sanofi, Servier. Solange Peters reports consultation/advisory role: AbbVie, Amgen, AstraZeneca, Bayer, Beigene, Biocartis, Bio Invent, Blueprint Medicines, Boehringer Ingelheim, Bristol-Myers Squibb, Clovis, Daiichi Sankyo, Debiopharm, Eli Lilly, Elsevier, F. Hoffmann-La Roche/Genentech, Foundation Medicine, Illumina, Incyte, IQVIA, Janssen, Medscape, Merck Sharp and Dohme, Merck Serono, Merrimack, Mirati, Novartis, Pharma Mar, Phosplatin Therapeutics, Pfizer, Regeneron, Sanofi, Seattle Genetics, Takeda, Vaccibody, talk in a company’s organized public event: AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, e-cancer, Eli Lilly, F. Hoffmann-La Roche/Genentech, Illumina, Medscape, Merck Sharp and Dohme, Novartis, PER, Pfizer, Prime, RTP, Sanofi, Takeda, receipt of grants/research supports: (Sub)investigator in trials (institutional financial support for clinical trials) sponsored by Amgen, AstraZeneca, Biodesix, Boehringer Ingelheim, Bristol-Myers Squibb, Clovis, F. Hoffmann-La Roche/Genentech, GSK, Illumina, Lilly, Merck Sharp and Dohme, Merck Serono, Mirati, Novartis, and Pfizer, Phosplatin Therapeutics. M Rowe honoraria from Astellas Pharma, speaker fees MSD and Servier. C. Wilson consultancy and speaker fees Pfizer, Amgen, Novartis, A Armstrong conference fee Merck, spouse shares in Astrazeneca. T Robinson financial support to attend educational workshops from Amgen and Daiichi-Sankyo. C Dive, outside of this scope of work, has received research funding from AstraZeneca, Astex Pharmaceuticals, Bioven, Amgen, Carrick Therapeutics, Merck AG, Taiho Oncology, Clearbridge Biomedics, Angle PLC, Menarini Diagnostics, GSK, Bayer, Boehringer Ingelheim, Roche, BMS, Novartis, Celgene, Thermofisher. C Dive is on advisory boards for, and has received consultancy fees/honoraria from, AstraZeneca, Biocartis and Merck KGaA. No other authors have nothing to declare. Ethics Approval Statement: Approval (reference 20/WA/0269) was granted from the UK Research Ethics Committee for the study. Information regarding governance/regulatory approvals for each international cohort are available in the Supp. Methods.

In this paper, we discuss the methodology of on-die simultaneous switching noise (SSN) simulation in high speed parallel bus like DDR5 associated with on-die capacitance and package inductance. The on-die supply ripple is typically larger than PCB power distribution network (PDN) noise even with a very good PCB PDN design. Resonance due to package inductance and on-die capacitance creates an impedance peak in the frequency domain and undesirable voltage noise in the time domain.

A simplified methodology for On-Die clock tree Power Supply Induced Jitter (PSIJ) analysis is put forth. The approach estimates jitter induced on a clock output (CK) without introducing significant error while significantly reducing simulation times. Approach relies on analysis of various transfer functions of on-die linear regulators. The accuracy of this simplified approach is highly dependent on on-die linear regulator design.

BackgroundCancer patients are at increased risk of severe COVID-19. As COVID-19 presentation and outcomes are heterogeneous in cancer patients, decision-making tools for hospital admission, severity prediction and increased monitoring for early intervention are critical.ObjectiveTo identify features of COVID-19 in cancer patients predicting severe disease and build a decision-support online tool; COVID-19 Risk in Oncology Evaluation Tool (CORONET)MethodData was obtained for consecutive patients with active cancer with laboratory confirmed COVID-19 presenting in 12 hospitals throughout the United Kingdom (UK). Univariable logistic regression was performed on pre-specified features to assess their association with admission (≥24 hours inpatient), oxygen requirement and death. Multivariable logistic regression and random forest models (RFM) were compared with patients randomly split into training and validation sets. Cost function determined cut-offs were defined for admission/death using RFM. Performance was assessed by sensitivity, specificity and Brier scores (BS). The CORONET model was then assessed in the entire cohort to build the online CORONET tool.ResultsTraining and validation sets comprised 234 and 66 patients respectively with median age 69 (range 19-93), 54% males, 46% females, 71% vs 29% had solid and haematological cancers. The RFM, selected for further development, demonstrated superior performance over logistic regression with AUROC predicting admission (0.85 vs. 0.78) and death (0.76 vs. 0.72). C-reactive protein was the most important feature predicting COVID-19 severity. CORONET cut-offs for admission and mortality of 1.05 and 1.8 were established. In the training set, admission prediction sensitivity and specificity were 94.5% and 44.3% with BS 0.118; mortality sensitivity and specificity were 78.5% and 57.2% with BS 0.364. In the validation set, admission sensitivity and specificity were 90.7% and 42.9% with BS 0.148; mortality sensitivity and specificity were 92.3% and 45.8% with BS 0.442. In the entire cohort, the CORONET decision support tool recommended admission of 99% of patients requiring oxygen and of 99% of patients who died.Conclusions and RelevanceCORONET, a decision support tool validated in hospitals throughout the UK showed promise in aiding decisions regarding admission and predicting COVID-19 severity in patients with cancer presenting to hospital. Future work will validate and refine the tool in further datasets.