Miracle-dz/UniFAR-FTUs huggingface dataset:
SDPS-47 CIRCULATING TUMOR CELL ANALYSIS FROM THE CEREBROSPINAL FLUID INFORMS EARLY DIAGNOSIS, TREATMENT AND PROGNOSIS IN LEPTOMENINGEAL CARCINOMATOSIS

Abstract INTRODUCTION Leptomeningeal carcinomatosis (LMC) is an aggressive pattern of recurrence with limited survival. Early detection by traditional CSF (cerebrospinal fluid) cytology is poor. We evaluated CSF circulating tumor cells (CTCs) with a commercially available assay (CNSideTM) and subsequent molecular profiling on captured CTCs, to determine if CTC analysis would lead to early detection, identification of therapeutic targets, and improved treatment outcomes. METHODS We analyzed 58 patients with carcinoma who were referred to Neuro-oncology clinic for evaluation for LMC, and underwent comprehensive work-up with CSF sampling (traditional cytology and CTCs), brain and spine MRI, and neurologic examination, and were followed for survival. RESULTS 28/58 were diagnosed with LMC (breast n=16, Lung n=9, other n=3). 24/28 were female. Median KPS was 80. 15/16 breast cancer patients were HER2- on initial systemic cancer diagnosis. The mean time to LMC from cancer diagnosis was 70 months. In the patients with LMC, CTCs were positive in 96%, compared to traditional cytology, which was positive in 64%. Molecular analysis of the CTCs in 15 patients with HER2- primary tumors detected HER2+ amplification in 3/15 patients. 14/28 patients received first line therapy for LMC with radiation + systemic chemotherapy + intrathecal chemotherapy, and 8/28 received systemic chemotherapy + intrathecal chemotherapy. 6/28 received other combinations. The overall median progression-free survival (PFS) was 5.3 months and the overall survival (OS) was 7.7 months from LMC diagnosis (breast PFS 4.5 months, OS 6.3 months; Lung PFS 5.3 months, OS 23.5 months). CONCLUSION CTC detection had superior sensitivity compared to traditional cytology, allowing for earlier detection of LMC and consequently earlier treatment. Molecular analysis of CTCs can allow for identification of therapeutic targets specific to the CSF, such as intrathecal trastuzumab for HER2+ LMC. PFS and OS in our cohort with this approach suggested improved survival compared to historical controls.
Impact of the COVID-19 Pandemic on the Severity and Early Postoperative Outcomes of Acute Appendicitis

Background The coronavirus disease 2019 (COVID-19) pandemic caused changes in surgical practice. For acute appendicitis (AA), measures to control the pandemic might hinder patients from seeking medical care timely, resulting in increasing severity, postoperative complications, and mortality. This study aimed to investigate whether the COVID-19 pandemic had a negative impact on the severity and postoperative outcomes of patients with AA. Methodology We retrospectively reviewed medical records of AA patients treated operatively at Nhan Dan Gia Dinh Hospital hospital from June 1st to September 30th in three consecutive years: pre-pandemic (2019)/Group 1, minor waves (2020)/Group 2, and major wave (2021)/Group 3 (2021). Data were collected focusing on the duration of symptoms, severity of AA, time from admission to operation, postoperative complications, and mortality. Results There were 1,055 patients, including 452 patients in Group 1, 409 in Group 2, and 194 in Group 3. The overall number of patients decreased mainly in non-complicated AA. The percentages of hospital admission after 24 hours gradually increased (20.8%, 27.9%, and 43.8%, p < 0.05). The percentages of complicated AA in Group 2 and Group 3 were statistically higher than in Group 1 (39% and 55% vs. 31%, p < 0.05). Waiting time for operation increased to five hours during the major wave. Laparoscopic appendectomy was performed in 98-99% of AA patients during the pandemic, with an early postoperative complication rate of 5-9% and a mortality rate of 0.2-1%. Conclusions Although the percentages of hospital admission after 24 hours and complicated AA increased, laparoscopic appendectomy was still feasible and effective and should be maintained as the standard management for AA during the COVID-19 pandemic.
Context-dependent memory recall in HMD-based immersive virtual environments

The article introduces an original VR-based experiment which explores context-dependent memory recall in humans. It specifically examines the recall of correct and falsely induced semantic memories. With the aid of VR head-mounted displays, 92 students of psychology were placed in a computer-generated indoor virtual environment and asked to memorize the presented lists of words. Afterwards, the participants were placed in the same indoor virtual environment or an alternative outdoor virtual environment and asked to recall the words. The number of correct and falsely induced words was then measured. On average, women recalled significantly more correct words from the list than men, regardless of the environmental context. Despite the assumptions, we did not observe a separate effect of exposure to different environments during learning and recall of material on memory performance. Likewise, we did not detect any effects of the learning context or biological sex in the case of the production of false memories. These results provide a novel insight into previous knowledge regarding the memory processes that occur in virtual environments. Although we failed to confirm the role of context in recalling learned material in general, we found a hint that this context might interact with specific memory processes of biological sexes. However, the design of this study only captured the effect of changing the environment during memory recall and did not address the role of specific context in remembering learning material. Further research is therefore needed to better investigate these phenomena and examine the role of biological sex in context-dependent memory processes.
Mathematical models for red squirrel conservation

In this thesis we develop mathematical models to understand the process of ecological invasion when the invading species also carries a disease that is harmful to the native species. In particular we focus on a key case study system of the invasion of grey squirrels and replacement of red squirrels in the UK, in which the shared disease, squirrelpox, has been suggested as a key driver of the rapid expansion of grey squirrels. Our initial study focused on examining the viability of red squirrels in the stronghold forests of Kidland and Uswayford in Northumberland. These are commercially managed forests that Forestry Commission England manage to improve red squirrel population viability. Through close collaboration with the Forestry Commission, we developed a mathematical model that could test squirrel population viability for a range of felling and replanting strategies. Our findings have been used to direct the forest design plans that will be implemented in these forests. Our second study used spatial, stochastic modelling techniques to model the replacement of red squirrels and subsequent control of grey squirrels on the Isle of Anglesey. Our findings indicated that the replacement of red squirrels by grey squirrels on the island was largely driven by competitive interactions. However, on a local level squirrelpox epidemics could occur and lead to mortality in red squirrel populations. Our model was also fitted to data on the control and eradication of grey squirrels and reintroduction of red squirrels that took place on the Isle of Anglesey between 1998-2013. Our fitted model was then used to examine the best conservation strategies to protect the red squirrels on Anglesey. Our final study compared key findings on the process of disease-mediated invasion in deterministic and stochastic model frameworks. The deterministic frameworks predict that a wave of disease can spread through a native population in advance of a wave of replacement of the invading species. A stochastic representation of this system indicated that this wave of disease in advance of the wave of replacement may not occur if the disease is too virulent to the native species. However, if the disease is supported by the invading species, it will still mediate the invasion at the interface between the native and invading species where local epidemic disease outbreaks can occur. In general this thesis shows that mathematical models are powerful tools for the conservation management of native species under threat from invasion.
Finite-size particles in turbulent channel flow: quadrant analysis and acceleration statistics

ABSTRACT The interaction between finite-size particles and turbulent channel flow in the absence of gravity is studied by direct numerical simulations (DNS). The study is motivated by DNS observations of a turbulent channel flow with high-density, pointwise particles, that cluster in regions of high streamwise root-mean-square (RMS) acceleration close to the wall, contrary to what is observed in homogeneous isotropic turbulence. The aim of the present study is to explore if this is still the case when size effects are taken into account in the DNS. Based on the analysis of the velocity and acceleration statistics, the present DNS shows that, close to the wall, particles with ρp/ρf ranging from 2 to 4 are surrounded by regions with low streamwise RMS velocity but high streamwise RMS acceleration. According to the normalised particle acceleration probability density functions (PDFs), size effects become important in the near-wall region. As particle inertia increases, the normalised PDFs of particle acceleration tend to a Gaussian distribution. The tails of the normalised PDFs of the fluid conditioned by the presence of particles are higher than that of the unconditioned fluid close to the wall.
A comparison of jade moxibustion and traditional moxibustion in the treatment of knee osteoarthritis: A randomized clinical trial

Background: This study was developed to compare the relative clinical efficacy of traditional moxibustion and Jade moxibustion in an effort to define the most effective approaches to treating knee osteoarthritis. Methods: In total, 94 patients were randomly assigned at a 1:1 ratio to the traditional moxibustion (TM) and Jade moxibustion (JM) groups. For JM, a jade kneepad was preheated for 3 minutes via electrification, with the jade in the kneepad being pressed onto acupoints when reaching an initial temperature of 46°C. For patients in the TM group, moxa cones were applied to acupoints for treatment. In total, 12 treatments were performed for patients in each group, with treatment being conducted 3 times per week. Study outcomes included 36-item short-form health survey and Western Ontario and McMaster Universities Osteoarthritis Index knee stiffness scores. In addition, serum levels of osteoarthritis-related cytokines were measured. Results: Overall, 89/94 patients completed this study, including 44 and 45 in the TM and JM groups, respectively. The 36-item short-form health survey physical functioning at weeks 12 and 24 (P = .033, 0.001), role-physical at weeks 4 and 24 (P = .030, 0.014), and role-emotional at week 4 (P = .045) were the only scores to differ significantly between the TM and JM groups. Western Ontario and McMaster Universities Osteoarthritis Index stiffness scores in the JM groups improved significantly relative to baseline at weeks 4, 8, 12, and 24 (all P < .01). The scores in the TM group differed significantly at all time points relative to baseline (all P < .01), with no differences between groups (all P > .05). Serum Interleukin-2 levels were lower in both groups (all P < .01). Cartilage oligomeric matrix protein and monocyte chemotactic protein-1 only differed significantly for patients treated via JM (P < .05, P < .01), with the same also being true for Interleukin-1β and Interleukin-8 in the TM group (all P < .01). No significant differences in other cytokines were observed, nor did they differ significantly between groups (all P > .05). Conclusion: These results suggest that JM treatment can improve knee osteoarthritis patient quality of life, alleviating joint stiffness and restoring joint function with a level of efficacy comparable to TM.
Small Area Estimation of Latent Economic Well-being

Small area estimation (SAE) plays a crucial role in the social sciences due to the growing need for reliable and accurate estimates for small domains. In the study of well-being, for example, policy makers need detailed information about the geographical distribution of a range of social indicators. We investigate data dimensionality reduction using factor analysis models and implement SAE on the factor scores under the empirical best linear unbiased prediction approach. We contrast this approach with the standard approach of providing a dashboard of indicators or a weighted average of indicators at the local level. We demonstrate the approach in a simulation study and a real data application based on the European Union Statistics for Income and Living Conditions for the municipalities of Tuscany.
Distributed CSIT Does Not Reduce the Generalized DoF of the 2-User MISO Broadcast Channel

In this letter we analyze the high signal-to-noise ratio regime performance of the multi-transmitter MISO broadcast channel with so-called distributed channel state information at the transmitters (CSIT), i.e., where CSIT is made transmitter-dependent. Specifically, we show the unexpected result that it is possible to achieve the same generalized degrees-of-freedom independently of whether a channel link estimate is present at one transmitter (TX), at the other TX, or at both, and regardless of the channel pathloss topology, thanks to a novel transmission scheme. The proposed scheme involves as key ingredient a new precoding scheme coined sliced zero-forcing which efficiently adapts to any distributed CSIT setting.
Randomised controlled trial of integrated care to reduce disability from chronic low back pain in working and private life

Objective To evaluate the effectiveness of an integrated care programme, combining a patient directed and a workplace directed intervention, for patients with chronic low back pain. Design Population based randomised controlled trial. Setting Primary care (10 physiotherapy practices, one occupational health service, one occupational therapy practice) and secondary care (five hospitals). Participants 134 adults aged 18-65 sick listed for at least 12 weeks owing to low back pain. Intervention Patients were randomly assigned to usual care (n=68) or integrated care (n=66). Integrated care consisted of a workplace intervention based on participatory ergonomics, involving a supervisor, and a graded activity programme based on cognitive behavioural principles. Main outcome measures The primary outcome was the duration of time off work (work disability) due to low back pain until full sustainable return to work. Secondary outcome measures were intensity of pain and functional status. Results The median duration until sustainable return to work was 88 days in the integrated care group compared with 208 days in the usual care group (P=0.003). Integrated care was effective on return to work (hazard ratio 1.9, 95% confidence interval 1.2 to 2.8, P=0.004). After 12 months, patients in the integrated care group improved significantly more on functional status compared with patients in the usual care group (P=0.01). Improvement of pain between the groups did not differ significantly. Conclusion The integrated care programme substantially reduced disability due to chronic low back pain in private and working life. Trial registration Current Controlled Trials ISRCTN28478651.
Pathology of myelin oligodendrocyte glycoprotein antibody-associated disease: a comparison with multiple sclerosis and aquaporin 4 antibody-positive neuromyelitis optica spectrum disorders

Myelin oligodendrocyte glycoprotein (MOG) is expressed on the outermost layer of the myelin sheath in the central nervous system. Recently, the clinical concept of MOG antibody-associated disease (MOGAD) was established based on the results of human MOG-transfected cell-based assays which can detect conformation-sensitive antibodies against MOG. In this review, we summarized the pathological findings of MOGAD and discussed the issues that remain unresolved. MOGAD pathology is principally inflammatory demyelination without astrocyte destruction, characterized by perivenous demyelination previously reported in acute disseminated encephalomyelitis and by its fusion pattern localized in both the white and gray matter, but not by radially expanding confluent demyelination typically seen in multiple sclerosis (MS). Some of demyelinating lesions in MOGAD show severe loss of MOG staining compared with those of other myelin proteins, suggesting a MOG-targeted pathology in the disease. Perivascular cuffings mainly consist of macrophages and T cells with CD4-dominancy, which is also different from CD8+ T-cell-dominant inflammation in MS. Compared to aquaporin 4 (AQP4) antibody-positive neuromyelitis optica spectrum disorders (NMOSD), perivenous complement deposition is less common, but can be seen on myelinated fibers and on myelin degradation products within macrophages, resembling MS Pattern II pathology. Thus, the pathogenetic contribution of complements in MOGAD is still debatable. Together, these pathological features in MOGAD are clearly different from those of MS and AQP4 antibody-positive NMOSD, suggesting that MOGAD is an independent autoimmune demyelinating disease entity. Further research is needed to clarify the exact pathomechanisms of demyelination and how the pathophysiology relates to the clinical phenotype and symptoms leading to disability in MOGAD patients.
ELB-trees - Efficient Lock-free B+trees

As computer systems scale in the number of processors, data structures with good parallel performance become increasingly important. Lock-free data structures promise improved parallel performance at the expense of higher complexity and sequential execution time. We present ELB-trees, a new lock-free dictionary with simple synchronization in the common case, making it almost 30 times faster than sequential library implementations at 24 threads.
L G ] 2 6 A pr 2 01 9 Stability and Optimization Error of Stochastic Gradient Descent for Pairwise Learning

In this paper we study the stability and its trade-off with optimization error for stochastic gradient descent (SGD) algorithms in the pairwise learning setting. Pairwise learning refers to a learning task which involves a loss function depending on pairs of instances among which notable examples are bipartite ranking, metric learning, area under ROC (AUC) maximization and minimum error entropy (MEE) principle. Our contribution is twofold. Firstly, we establish the stability results of SGD for pairwise learning in the convex, strongly convex and non-convex settings, from which generalization bounds can be naturally derived. Secondly, we establish the trade-off between stability and optimization error of SGD algorithms for pairwise learning. This is achieved by lower-bounding the sum of stability and optimization error by the minimax statistical error over a prescribed class of pairwise loss functions. From this fundamental trade-off, we obtain lower bounds for the optimization error of SGD algorithms and the excess expected risk over a class of pairwise losses. In addition, we illustrate our stability results by giving some specific examples of AUC maximization, metric learning and MEE.
Convolutional Simplex Projection Network (CSPN) for Weakly Supervised Semantic Segmentation

Weakly supervised semantic segmentation has been a subject of increased interest due to the scarcity of fully annotated images. We introduce a new approach for solving weakly supervised semantic segmentation with deep Convolutional Neural Networks (CNNs). The method introduces a novel layer which applies simplex projection on the output of a neural network using area constraints of class objects. The proposed method is general and can be seamlessly integrated into any CNN architecture. Moreover, the projection layer allows strongly supervised models to be adapted to weakly supervised models effortlessly by substituting ground truth labels. Our experiments have shown that applying such an operation on the output of a CNN improves the accuracy of semantic segmentation in a weakly supervised setting with image-level labels.
Drag of a heated sphere at low Reynolds numbers in the absence of buoyancy

Fully resolved simulations are used to quantify the effects of heat transfer in the absence of buoyancy on the drag of a spatially fixed heated spherical particle at low Reynolds numbers ( $Re$ ) in the range $10^{-3}\leqslant Re\leqslant 10$ in a variable-property fluid. The case where buoyancy is present is analysed in a subsequent paper. This analysis is carried out without making any assumptions on the amount of heat addition from the sphere and thus encompasses both the heating regime where the Boussinesq approximation holds and the regime where it breaks down. The particle is assumed to have a low Biot number, which means that the particle is uniformly at the same temperature and has no internal temperature gradients. Large deviations in the value of the drag coefficient as the temperature of the sphere increases are observed. When $Re<O(10^{-2})$ , these deviations are explained using a low-Mach-number perturbation analysis as irrotational corrections to a Stokes–Oseen base flow. Correlations for the drag and Nusselt number of a heated sphere are proposed for the range of Reynolds numbers $10^{-3}\leqslant Re\leqslant 10$ which fit the computationally obtained values with less than 1 % and 3 % errors, respectively. These correlations can be used in simulations of gas–solid flows where the accuracy of the drag law affects the prediction of the overall flow behaviour. Finally, an analogy to incompressible flow over a modified sphere is demonstrated.
Photometric detection of internal gravity waves in upper main-sequence stars

Context. Massive stars are predicted to excite internal gravity waves (IGWs) by turbulent core convection and from turbulent pressure fluctuations in their near-surface layers. These IGWs are extremely efficient at transporting angular momentum and chemical species within stellar interiors, but they remain largely unconstrained observationally. Aims. We aim to characterise the photometric detection of IGWs across a large number of O and early-B stars in the Hertzsprung–Russell diagram, and explain the ubiquitous detection of stochastic variability in the photospheres of massive stars. Methods. We combined high-precision time-series photometry from the NASA Transiting Exoplanet Survey Satellite with high-resolution ground-based spectroscopy of 70 stars with spectral types O and B to probe the relationship between the photometric signatures of IGWs and parameters such as spectroscopic mass, luminosity, and macroturbulence. Results. A relationship is found between the location of a star in the spectroscopic Hertzsprung–Russell diagram and the amplitudes and frequencies of stochastic photometric variability in the light curves of massive stars. Furthermore, the properties of the stochastic variability are statistically correlated with macroturbulent velocity broadening in the spectral lines of massive stars. Conclusions. The common ensemble morphology for the stochastic low-frequency variability detected in space photometry and its relationship to macroturbulence is strong evidence for IGWs in massive stars, since these types of waves are unique in providing the dominant tangential velocity field required to explain the observed spectroscopy.