Enterobius vermicularis in the male urinary tract: a case report

Enterobius vermicularis is an intestinal nematode of humans. Adults usually have low worm burdens and are asymptomatic. Ectopic infections in the pelvic area or urinary tract rarely occur in women. We report a case of the patient with mild voiding difficulties such as urgency, frequency, nocturia, dysuria, mild low back pain or perineal discomfort. The patient's prostatic secretions showed a large number of inflammatory cells and several eggs. The size and the shape of the eggs identified them as a group of E. vermicularis. On examination we found a soft palpable material which was 5 mm diameter in size and spherical shape. Palpation gave the impression of a tissue than a stone. An incision was performed and a 4 mm long living worm was found. The microscopic examination identified the worm as E- vermicularis. It is an extremely rare manifestation of enterobius vermicularis infection since an intestinal-breeding worm is rarely found in the male genital tract

Magnetars and pulsars: a missing link

There is growing evidence that soft gamma-ray repeaters (SGRs) and anomalous X-ray pulsars (AXPs) are isolated neutron stars with superstrong magnetic fields, i.e., magnetars, marking them a distinguished species from the conventional species of spindown-powered isolated neutron stars, i.e., radio pulsars. The current arguments in favor of the magnetar interpretation of SGR/AXP phenomenology will be outlined, and the two energy sources in magnetars, i.e. a magnetic dissipation energy and a spindown energy, will be reviewed. I will then discuss a missing link between magnetars and pulsars, i.e., lack of the observational evidence of the spindown-powered behaviors in known magnetars. Some recent theoretical efforts in studying such behaviors will be reviewed along with some predictions testable in the near future.Comment: Invited talk at the Sixth Pacific Rim Conference on Stellar Astrophysics, a tribute to Helmut A. Abt, July 11-17, 2002, Xi'an. To appear in the proceedings (eds. K. S. Cheng, K. C. Leung & T. P. Li

Midgut microbiota of the malaria mosquito vector Anopheles gambiae and Interactions with plasmodium falciparum Infection

The susceptibility of Anopheles mosquitoes to Plasmodium infections relies on complex interactions between the insect vector and the malaria parasite. A number of studies have shown that the mosquito innate immune responses play an important role in controlling the malaria infection and that the strength of parasite clearance is under genetic control, but little is known about the influence of environmental factors on the transmission success. We present here evidence that the composition of the vector gut microbiota is one of the major components that determine the outcome of mosquito infections. A. gambiae mosquitoes collected in natural breeding sites from Cameroon were experimentally challenged with a wild P. falciparum isolate, and their gut bacterial content was submitted for pyrosequencing analysis. The meta-taxogenomic approach revealed a broader richness of the midgut bacterial flora than previously described. Unexpectedly, the majority of bacterial species were found in only a small proportion of mosquitoes, and only 20 genera were shared by 80% of individuals. We show that observed differences in gut bacterial flora of adult mosquitoes is a result of breeding in distinct sites, suggesting that the native aquatic source where larvae were grown determines the composition of the midgut microbiota. Importantly, the abundance of Enterobacteriaceae in the mosquito midgut correlates significantly with the Plasmodium infection status. This striking relationship highlights the role of natural gut environment in parasite transmission. Deciphering microbe-pathogen interactions offers new perspectives to control disease transmission.Institut de Recherche pour le Developpement (IRD); French Agence Nationale pour la Recherche [ANR-11-BSV7-009-01]; European Community [242095, 223601]info:eu-repo/semantics/publishedVersio

Excess risk of adverse pregnancy outcomes in women with porphyria: a population-based cohort study

The porphyrias comprise a heterogeneous group of rare, primarily hereditary, metabolic diseases caused by a partial deficiency in one of the eight enzymes involved in the heme biosynthesis. Our aim was to assess whether acute or cutaneous porphyria has been associated with excess risks of adverse pregnancy outcomes. A population-based cohort study was designed by record linkage between the Norwegian Porphyria Register, covering 70% of all known porphyria patients in Norway, and the Medical Birth Registry of Norway, based on all births in Norway during 1967–2006. The risks of the adverse pregnancy outcomes preeclampsia, delivery by caesarean section, low birth weight, premature delivery, small for gestational age (SGA), perinatal death, and congenital malformations were compared between porphyric mothers and the rest of the population. The 200 mothers with porphyria had 398 singletons during the study period, whereas the 1,100,391 mothers without porphyria had 2,275,317 singletons. First-time mothers with active acute porphyria had an excess risk of perinatal death [adjusted odds ratio (OR) 4.9, 95% confidence interval (CI) 1.5–16.0], as did mothers with the hereditable form of porphyria cutanea tarda (PCT) (3.0, 1.2–7.7). Sporadic PCT was associated with an excess risk of SGA [adjusted relative risk (RR) 2.0, 1.2–3.4], and for first-time mothers, low birth weight (adjusted OR 3.4, 1.2–10.0) and premature delivery (3.5, 1.2–10.5) in addition. The findings suggest women with porphyria should be monitored closely during pregnancy

Vibro-Injection Pile Installation in Sand: Part I—Interpretation as Multi-material Flow

The installation of vibro-injection piles into saturated sand has a significant impact on the surrounding soil and neighboring buildings. It is generally characterized by a multi-material flow with large material deformations, non-stationary and new material interfaces, and by the interaction of the grain skeleton and the pore water. Part 1 in this series of papers is concerned with the mathematical and physical modeling of the multi-material flow associated with vibro-injection pile installation. This model is the backbone of a new multi-material arbitrary Lagrangian-Eulerian (MMALE) numerical method presented in Part 2.DFG, 76838227, Numerische Modellierung der Herstellung von Rüttelinjektionspfähle

NICE 2023 Zero-shot Image Captioning Challenge

In this report, we introduce NICE project\footnote{\url{https://nice.lgresearch.ai/}} and share the results and outcomes of NICE challenge 2023. This project is designed to challenge the computer vision community to develop robust image captioning models that advance the state-of-the-art both in terms of accuracy and fairness. Through the challenge, the image captioning models were tested using a new evaluation dataset that includes a large variety of visual concepts from many domains. There was no specific training data provided for the challenge, and therefore the challenge entries were required to adapt to new types of image descriptions that had not been seen during training. This report includes information on the newly proposed NICE dataset, evaluation methods, challenge results, and technical details of top-ranking entries. We expect that the outcomes of the challenge will contribute to the improvement of AI models on various vision-language tasks.Comment: Tech report, project page https://nice.lgresearch.ai

Measurement of the cross-section of high transverse momentum vector bosons reconstructed as single jets and studies of jet substructure in pp collisions at √s = 7 TeV with the ATLAS detector

This paper presents a measurement of the cross-section for high transverse momentum W and Z bosons produced in pp collisions and decaying to all-hadronic final states. The data used in the analysis were recorded by the ATLAS detector at the CERN Large Hadron Collider at a centre-of-mass energy of √s = 7 TeV;{\rm Te}{\rm V}$and correspond to an integrated luminosity of$4.6\;{\rm f}{{{\rm b}}^{-1}}$. The measurement is performed by reconstructing the boosted W or Z bosons in single jets. The reconstructed jet mass is used to identify the W and Z bosons, and a jet substructure method based on energy cluster information in the jet centre-of-mass frame is used to suppress the large multi-jet background. The cross-section for events with a hadronically decaying W or Z boson, with transverse momentum${{p}_{{\rm T}}}\gt 320\;{\rm Ge}{\rm V}$and pseudorapidity$|\eta |\lt 1.9$, is measured to be${{\sigma }_{W+Z}}=8.5\pm 1.7$ pb and is compared to next-to-leading-order calculations. The selected events are further used to study jet grooming techniques

Search for direct pair production of the top squark in all-hadronic final states in proton-proton collisions at s√=8 TeV with the ATLAS detector

The results of a search for direct pair production of the scalar partner to the top quark using an integrated luminosity of 20.1fb−1 of proton–proton collision data at √s = 8 TeV recorded with the ATLAS detector at the LHC are reported. The top squark is assumed to decay via t˜→tχ˜01 or t˜→ bχ˜±1 →bW(∗)χ˜01 , where χ˜01 (χ˜±1 ) denotes the lightest neutralino (chargino) in supersymmetric models. The search targets a fully-hadronic final state in events with four or more jets and large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits are reported in terms of the top squark and neutralino masses and as a function of the branching fraction of t˜ → tχ˜01 . For a branching fraction of 100%, top squark masses in the range 270–645 GeV are excluded for χ˜01 masses below 30 GeV. For a branching fraction of 50% to either t˜ → tχ˜01 or t˜ → bχ˜±1 , and assuming the χ˜±1 mass to be twice the χ˜01 mass, top squark masses in the range 250–550 GeV are excluded for χ˜01 masses below 60 GeV

Search for pair-produced long-lived neutral particles decaying to jets in the ATLAS hadronic calorimeter in ppcollisions at √s=8TeV

The ATLAS detector at the Large Hadron Collider at CERN is used to search for the decay of a scalar boson to a pair of long-lived particles, neutral under the Standard Model gauge group, in 20.3fb−1of data collected in proton–proton collisions at √s=8TeV. This search is sensitive to long-lived particles that decay to Standard Model particles producing jets at the outer edge of the ATLAS electromagnetic calorimeter or inside the hadronic calorimeter. No significant excess of events is observed. Limits are reported on the product of the scalar boson production cross section times branching ratio into long-lived neutral particles as a function of the proper lifetime of the particles. Limits are reported for boson masses from 100 GeVto 900 GeV, and a long-lived neutral particle mass from 10 GeVto 150 GeV

Improved general regression network for protein domain boundary prediction

Background: Protein domains present some of the most useful information that can be used to understand protein structure and functions. Recent research on protein domain boundary prediction has been mainly based on widely known machine learning techniques, such as Artificial Neural Networks and Support Vector Machines. In this study, we propose a new machine learning model (IGRN) that can achieve accurate and reliable classification, with significantly reduced computations. The IGRN was trained using a PSSM (Position Specific Scoring Matrix), secondary structure, solvent accessibility information and inter-domain linker index to detect possible domain boundaries for a target sequence. Results: The proposed model achieved average prediction accuracy of 67% on the Benchmark_2 dataset for domain boundary identification in multi-domains proteins and showed superior predictive performance and generalisation ability among the most widely used neural network models. With the CASP7 benchmark dataset, it also demonstrated comparable performance to existing domain boundary predictors such as DOMpro, DomPred, DomSSEA, DomCut and DomainDiscovery with 70.10% prediction accuracy. Conclusion: The performance of proposed model has been compared favourably to the performance of other existing machine learning based methods as well as widely known domain boundary predictors on two benchmark datasets and excels in the identification of domain boundaries in terms of model bias, generalisation and computational requirements. © 2008 Yoo et al; licensee BioMed Central Ltd