Miracle-dz/UniFAR-FTUs huggingface dataset:
Derotational Osteotomy of the Distal Femur for the Treatment of Patellofemoral Instability Simultaneously Leads to the Correction of Frontal Alignment: A Laboratory Cadaveric Study

Background: Derotational osteotomy of the distal femur allows the anatomic treatment of patellofemoral maltracking due to increased femoral antetorsion. However, such rotational osteotomy procedures have a high potential of intended/unintended changes of frontal alignment. Purpose/Hypothesis: The purpose of this study was to perform derotational osteotomy of the distal femur and to demonstrate the utility of a novel trigonometric approach to address 3-dimensional (3D) changes on 2-dimensional imaging (axial computed tomography [CT] and frontal-plane radiography). The hypothesis was that 1-step single-cut osteotomy can simultaneously correct torsion and frontal alignment based on preoperatively calculated cutting angles. Study Design: Controlled laboratory study. Methods: Eight human cadaveric whole legs (4 lower limb torsos) underwent derotational osteotomy of the distal femur of 20°. A straight leg axis, determined as a mechanical femorotibial angle (mFTA) of 0°, was chosen as a goal for postoperative frontal alignment. The inclination of the cutting angle from the lateral view was calculated individually for each cadaveric leg and was represented by a simple 3D-printed cutting guide for surgery. Specimens underwent CT for the measurement of torsion, while the frontal leg axis was determined on an upright radiograph preoperatively and postoperatively. Preoperative and postoperative angles were compared with the mathematical prediction model. Results: The preoperative mFTA ranged from –3.9° (valgus) to +3.4° (varus) (mean, –0.2° ± 2.6°). A postoperative mean mFTA of 0.37° ± 0.69° (95% CI, –0.22° to 0.95°) was achieved (P = .01). Derotation showed a mean of 19.1° ± 2.1° (95% CI, 17.3°-20.8°). The oblique cutting plane for the correction of valgus legs showed a mean of 5.9° ± 6.8° and, for the correction of varus legs, a mean of –10.0° ± 4.5° projected on the perpendicular plane to the virtual anatomic shaft axis from the sagittal view. Conclusion: Single-cut distal femoral osteotomy can be performed to simultaneously address rotational as well as frontal alignment using a preoperatively defined oblique cut, as determined by the presented reproducible calculation model. Clinical Relevance: This study adds important knowledge to the technique of derotational osteotomy. This approach provides an individual, oblique single cut for the correction of torsion and frontal axis within a clinically insignificant margin. Simplified tables for calculation and a surgical reference make this model reproducible and safe.
Stable Local Broadcast in Multihop Wireless Networks Under SINR

We present a distributed stable protocol for local broadcast in multi-hop wireless networks, where packets are injected to the nodes continuously, and each node needs to quickly disseminate the injected packets to all its neighbors within a given communication range $R$ . We investigate the maximum packet injection rate and the minimum packet latency that can be achieved in a stable protocol. This paper assumes the signal-to-interference-plus-noise-ratio (SINR) interference model, which reflects more accurately the physical characteristics of the wireless interference, such as fading and signal accumulation, than conventional local interference models, e.g., graph-based models. More specifically, we present a stable protocol that can handle both stochastic and adversarial injection patterns. The protocol is asymptotically optimal in terms of both injection rate and packet latency. To the best of our knowledge, this paper is the first one studying the properties of stable protocols for the basic primitive of local broadcast in a multi-hop setting under SINR. Our proposed protocol utilizes a static local broadcast algorithm as a subroutine. This static algorithm is of independent interest, and it closes the $O(\log n)$ gap between the upper and lower bounds for static local broadcast. Simulation results indicate that our proposed algorithms can perform well in realistic environments.
“Fleeting pulmonary infiltrates in allergic bronchopulmonary aspergillosis” Misdiagnosed as tuberculosis

Allergic bronchopulmonary aspergillosis (ABPA) is underdiagnosed and underevaluated routinely because of clinical and radiological overlap with tuberculosis (TB), especially in tropical setting with high TB burden countries like India. ABPA is the best-recognized manifestation of Aspergillus-associated hypersensitivity to Aspergillus antigens in patients with long-standing atopic asthma. ABPA with varied clinical presentation has been reported to occur in 20% of asthmatic patients admitted to hospitals and in 5% of all rhinitis cases. In this case report, we documented middle age male with known asthma case for many years with constitutional symptoms such as cough, fever, and shortness of breath diagnosed as TB and received anti-TB treatment for 4 weeks. Finally, we confirmed as a case of ABPA and documented complete clinical and radiological response to medical treatment with antifungals and systemic corticosteroids.
Determinants of physiological uptake of 18F-fluorodeoxyglucose in palatine tonsils

Abstract To determine the extent of physiological variation of uptake of 18F-flurodeoxyglucose (FDG) within palatine tonsils. To define normal limits for side-to-side variation and characterize factors affecting tonsillar uptake of FDG. Over a period of 16 weeks 299 adult patients at low risk for head and neck pathology, attending our center for FDG positron emission tomography/computed tomography (PET/CT) scans were identified. The maximum standardized uptake value (SUVmax) was recorded for each palatine tonsil. For each patient age, gender, smoking status, scan indication and prior tonsillectomy status as well as weather conditions were noted. There was a wide variation in palatine tonsil FDG uptake with SUVmax values between 1.3 and 11.4 recorded. There was a strong left to right correlation for tonsillar FDG uptake within each patient (P < .01). The right palatine tonsil showed increased FDG uptake (4.63) compared to the left (4.47) (P < .01). In multivariate analysis, gender, scan indication, and prevailing weather had no significant impact of tonsillar FDG uptake. Lower tonsillar uptake was seen in patients with a prior history of tonsillectomy (4.13) than those without this history (4.64) (P < .01). Decreasing tonsillar FDG uptake was seen with advancing age (P < .01). Significantly lower uptake was seen in current smokers (SUVmax 4.2) than nonsmokers (SUV 4.9) (P = .03). Uptake of FDG in palatine tonsils is variable but shows a strong side-to-side correlation. We suggest the left/ right SUVmax ratio as a guide to normality with a first to 99th percentiles of (0.70–1.36) for use in patients not suspected to have tonsillar pathology.
Increase in PD-L1 expression after pre-operative radiotherapy for soft tissue sarcoma

ABSTRACT Soft tissue sarcomas (STS) have minimal expression of PD-L1, a biomarker for PD-1 therapy efficacy. Radiotherapy (RT) has been shown to increase PD-L1 expression pre-clinically. We examined the expression of PD-L1, pre- and post-RT, in 46 Stage II-III STS patients treated with pre-operative RT (50–50.4 Gy in 25–28 fractions) followed by resection. Five additional patients who did not receive RT were utilized as controls. PD-L1 expression on biopsy and resection samples was evaluated by immunochemistry using the anti PD-L1 monoclonal antibody (E1L3 N clone; Cell Signaling). Greater than 1% membranous staining was considered positive PD-L1 expression. Changes in PD-L1 expression were analyzed via the Fisher exact test. Kaplan-Meier statistics were used to correlate PD-L1 expression to distant metastases (DM) rate. The majority of STS were T2b (87.0%), high-grade (80.4%), undifferentiated pleomorphic histology (71.7%), and originated from the extremities (84.6%). Zero patients demonstrated PD-L1 tumor expression pre-RT. Post-RT, 5 patients (10.9%) demonstrated PD-L1 tumor expression (p = 0.056). Tumor associated macrophages (TAM) expression of PD-L1 increased after RT: 15.2% to 45.7% (p = 0.003). Samples from controls demonstrated no baseline (0%) or change in tumor PD-L1 expression. Freedom from DM was lower for patients with PD-L1 TAM expression post-RT (3 years: 49.7% vs. 87.8%, log-rank p = 0.006); TAM PD-L1 positivity remained an independent predictor for DM on multivariate analyses (Hazard ratio – 0.16, 95% confidence interval: 0.034–0.721, p = 0.042). PD-L1 expression on human STS tumor and TAM appears to elevate after pre-operative RT. Expression of PD-L1 on TAM after RT was associated with a higher rate of DM.
Patterns of solid particle embolization during transcatheter aortic valve implantation and correlation with aortic valve calcification

OBJECTIVES To evaluate solid embolization during transcatheter aortic valve implantation (TAVI) and correlate this with aortic valve calcification. BACKGROUND There is a known stroke risk with TAVI, thought partly to be due to dislodgement of native aortic valve particles during implantation. However, to date there is little evidence that aortic valve calcification actually impacts embolic risk. METHODS Transcranial Doppler (TCD) was performed on consecutive suitable patients undergoing TAVI, using hardware and software enabling differentiation between solid and gaseous emboli. Data was analyzed by time points during the TAVI procedure. These results were correlated with aortic valve calcification. RESULTS TCD was successfully performed on 63 patients. The median number of solid emboli was 76.0. The most common time point for solid embolization was during valve positioning. Forty-five of these patients had an appropriate CT scan which could be analyzed for an Agatston calcium score. The mean scores in the aortic valve and aortic root were 3382.4 and 754.9. There were significant correlations between the total number of solid emboli and valve calcium score (P = 0.033) and solid emboli during valve positioning and valve calcium score (P = 0.035). There was no relationship between gaseous emboli and valve calcium score. CONCLUSIONS TAVI is associated with significant solid particle embolization, with the most common time point being during valve positioning. Solid embolization correlates with aortic valve calcium score, suggesting that valve calcification is a factor in embolic risk. This should be taken into consideration along with other clinical factors when assessing embolic risk.
Spatial-mode multiplexing with mutually coherent channels in free space optical communications

In this paper, the spatial-mode multiplexing (SMM) free-space optical communication (FSO) systems with direct detection are considered. Unlike systems studied in several works in the literature where mutually incoherent channels are assumed, we investigate high-speed SMM FSO systems with mutually coherent channels where a single laser source with narrow linewidth is employed at the transmitter. An analytical model for such mutually coherent channels is developed and expression for aggregate achievable rate (AAR) is derived. Through numerical simulations, it is shown that an optimal transmitted mode set can be determined which results in the maximal asymptotic AAR at high transmitted power and for different turbulence conditions, the optimal mode set varies.
Probabilistic-Input, Noisy Conjunctive Models for Cognitive Diagnosis

Existing cognitive diagnosis models conceptualize attribute mastery status discretely as either mastery or non-mastery. This study proposes a different conceptualization of attribute mastery as a probabilistic concept, i.e., the probability of mastering a specific attribute for a person, and developing a probabilistic-input, noisy conjunctive (PINC) model, in which the probability of mastering an attribute for a person is a parameter to be estimated from data. And a higher-order version of the PINC model is used to consider the associations among attributes. The results of simulation studies revealed a good parameter recovery for the new models using the Bayesian method. The Examination for the Certificate of Proficiency in English (ECPE) data set was analyzed to illustrate the implications and applications of the proposed models. The results indicated that PINC models had better model-data fit, smaller item parameter estimates, and more refined estimates of attribute mastery.
DRUGS IN CONTEXT RIGOROUS • RAPID

Hypertension is a major preventable risk factor for atherosclerosis and ischemic heart disease. Although modern and effective antihypertensive drugs are available, most patients remain with a suboptimal blood pressure control. Most hypertensive patients will need a combination of antihypertensive agents to achieve the therapeutic goals – recent guidelines recommend initiating treatment with two drugs in those patients with a systolic blood pressure >20 mmHg and/or a diastolic blood pressure >10 mmHg above the goals, and in those patients with high cardiovascular risk. In addition, approximately 25% of patients will require three antihypertensive agents to achieve the therapeutic targets. In this review, we analyse the latest information available regarding the treatment of hypertension with combination therapy.
Molecular dynamics study of carbon nanotube/graphene reinforced nickel composites

Single layer graphene sheets (SLGS) and carbon nanotubes (CNTs) have resulted in the development of new materials for variety of applications. In this study, molecular dynamics (MD) simulation has been used to assess this issue. Materials Studio 7.0 has been used as a tool for finding the modulus and thermal conductivity of nanocomposites. Two different computational models, SLGS/nickel and CNT/nickel composites have been examined to study the effect of nanofiller geometry on Young's modulus and thermal conductivity of these nanocomposites. The effect of nanofiller volume fraction (Vj) on Young's modulus and thermal conductivity has also been studied. Results show that with increase in Vj the Young's modulus as well as thermal conductivity of SLGS/Ni composites increases at a faster rate than for CNT/Ni composite. For same Vj, Young's modulus of SLGS/Ni composite is higher than CNT/Ni composite, showing that SLGS is a better reinforcement than CNT for Ni based composites.
Predicting HLA CD4 Immunogenicity in Human Populations

Background Prediction of T cell immunogenicity is a topic of considerable interest, both in terms of basic understanding of the mechanisms of T cells responses and in terms of practical applications. HLA binding affinity is often used to predict T cell epitopes, since HLA binding affinity is a key requisite for human T cell immunogenicity. However, immunogenicity at the population it is complicated by the high level of variability of HLA molecules, potential other factors beyond HLA as well as the frequent lack of HLA typing data. To overcome those issues, we explored an alternative approach to identify the common characteristics able to distinguish immunogenic peptides from non-recognized peptides. Methods Sets of dominant epitopes derived from peer-reviewed published papers were used in conjunction with negative peptides from the same experiments/donors to train neural networks and generate an “immunogenicity score. ” We also compared the performance of the immunogenicity score with previously described method for immunogenicity prediction based on HLA class II binding at the population level. Results The immunogenicity score was validated on a series of independent datasets derived from the published literature, representing 57 independent studies where immunogenicity in human populations was assessed by testing overlapping peptides spanning different antigens. Overall, these testing datasets corresponded to over 2,000 peptides and tested in over 1,600 different human donors. The 7-allele method prediction and the immunogenicity score were associated with similar performance [average area under the ROC curve (AUC) values of 0.703 and 0.702, respectively] while the combined methods reached an average AUC of 0.725. This increase in average AUC value is significant compared with the immunogenicity score (p = 0.0135) and a strong trend toward significance is observed when compared to the 7-allele method (p = 0.0938). The new immunogenicity score method is now freely available using CD4 T cell immunogenicity prediction tool on the Immune Epitope Database website (http://tools.iedb.org/CD4episcore). Conclusion The new immunogenicity score predicts CD4 T cell immunogenicity at the population level starting from protein sequences and with no need for HLA typing. Its efficacy has been validated in the context of different antigen sources, ethnicities, and disparate techniques for epitope identification.
Can a 1-D mantle electrical conductivity model generate magnetic jerk differential time delays?

SUMMARY Worldwide jerks occurring in 1969, 1978 and 1991 are not simultaneous at the earth’s surface, showing differential delays of about 2 yr. One way to explain this intriguing temporal pattern is to consider the earth’s mantle as a conductor. Consequently the geomagnetic field observed at the earth’s surface will correspond to a filtered version of the original field generated at the core‐mantle boundary (CMB). We developed the forward approach to this problem assuming the temporal part of the jerk as a simultaneous impulse in the third time-derivative of the magnetic field at the CMB. Two synthetic spherical harmonic models of the jerk amplitudes are built by using two different power spectra. The effect of the mantle is illustrated by a 1-D radial electrical conductivity model that acts as linear, causal and time-invariant filter. The key point is that the mantle filter is different for each harmonic degree. Therefore, because the mixing of harmonics varies with location, distinct time delays will exist at the earth’s surface. By using Backus’ mantle filter theory, we demonstrate that a simple 1-D mantle electrical conductivity model is able to generate differential jerk time delays that depend strongly on the jerk morphology input model. We also illustrate that the time delays will vary for each component of the magnetic field.
Awake animal functional imaging to investigate the effects of general anesthesia on brain

General anesthesia has been performed reliably for nearly 170 years even though its exact mechanism is still unknown. To date, almost all small animal studies to investigate the effects of general anesthesia have been done under anesthesia and it prevents the quantitative analysis because of anesthesia itself effects the neurofunctional parameters under study. Here we have used an awake animal imaging method to study and compare cerebral glucose utilization in the awake and anesthetized states. We have shown that the general anesthesia has a profound effect on rat brain and it depends on the type and the dose of anesthetic drug.
The neuronal perceptron with DNA strand displacement

In the field of biologic computing and neural networks, DNA strand displacement technology performs well in computing, programming and information processing. In this paper, based on two-domain DNA strand displacement, the neural DNA perceptron is proposed to implement Boolean operations. Some operation instances are simulated by Visual DSD (DNA strand displacement) software in which details of simulation process were presented. Our results showed that the precision of the neural DNA perceptron is higher than that of a bio-sensor designed by Shi et al. Furthermore, extrapolating from the neural DNA perceptron, we presented a multi-bit numerical comparator to achieve multi-bit numerical comparisons, which received stable and intuitive simulation results. The neural DNA perceptron and the multi-bit numerical comparator are easy to operate and achieve satisfactory effects.
Virtual Network Function Placement Considering Resource Optimization and SFC Requests in Cloud Datacenter

Network function virtualization (NFV) brings great conveniences and benefits for the enterprises to outsource their network functions to the cloud datacenter. In this paper, we address the virtual network function (VNF) placement problem in cloud datacenter considering users’ service function chain requests (SFCRs). To optimize the resource utilization, we take two less-considered factors into consideration, which are the time-varying workloads, and the basic resource consumptions (BRCs) when instantiating VNFs in physical machines (PMs). Then the VNF placement problem is formulated as an integer linear programming (ILP) model with the aim of minimizing the number of used PMs. Afterwards, a Two-StAge heurisTic solution (T-SAT) is designed to solve the ILP. T-SAT consists of a correlation-based greedy algorithm for SFCR mapping (first stage) and a further adjustment algorithm for virtual network function requests (VNFRs) in each SFCR (second stage). Finally, we evaluate T-SAT with the artificial data we compose with Gaussian function and trace data derived from Google's datacenters. The simulation results demonstrate that the number of used PMs derived by T-SAT is near to the optimal results and much smaller than the benchmarks. Besides, it improves the network resource utilization significantly.
Generating synthetic CTs from magnetic resonance images using generative adversarial networks

PURPOSE While MR-only treatment planning using synthetic CTs (synCTs) offers potential for streamlining clinical workflow, a need exists for an efficient and automated synCT generation in the brain to facilitate near real-time MR-only planning. This work describes a novel method for generating brain synCTs based on generative adversarial networks (GANs), a deep learning model that trains two competing networks simultaneously, and compares it to a deep convolutional neural network (CNN). METHODS Post-Gadolinium T1-Weighted and CT-SIM images from fifteen brain cancer patients were retrospectively analyzed. The GAN model was developed to generate synCTs using T1-weighted MRI images as the input using a residual network (ResNet) as the generator. The discriminator is a CNN with five convolutional layers that classified the input image as real or synthetic. Fivefold cross-validation was performed to validate our model. GAN performance was compared to CNN based on mean absolute error (MAE), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR) metrics between the synCT and CT images. RESULTS GAN training took ~11 h with a new case testing time of 5.7 ± 0.6 s. For GAN, MAEs between synCT and CT-SIM were 89.3 ± 10.3 Hounsfield units (HU) and 41.9 ± 8.6 HU across the entire FOV and tissues, respectively. However, MAE in the bone and air was, on average, ~240-255 HU. By comparison, the CNN model had an average full FOV MAE of 102.4 ± 11.1 HU. For GAN, the mean PSNR was 26.6 ± 1.2 and SSIM was 0.83 ± 0.03. GAN synCTs preserved details better than CNN, and regions of abnormal anatomy were well represented on GAN synCTs. CONCLUSIONS We developed and validated a GAN model using a single T1-weighted MR image as the input that generates robust, high quality synCTs in seconds. Our method offers strong potential for supporting near real-time MR-only treatment planning in the brain.