Rituximab induced hypoglycemia in non-Hodgkin's lymphoma

BACKGROUND: Hypoglycemia is a vary rare toxicity of rituximab. The exact mechanism of rituximab induced hypoglycemia is not clear. CASE PRESENTATION: A 50 year old female presented with a left tonsillar non Hodgkin's lymphoma and was started on R-CHOP chemotherapy. Twenty four hours after the first rituximab infusion, she developed hypoglycemia which was managed by IV glucose infusion. CONCLUSION: Hypoglycemia following rituximab administration is rare. Possibilities of hypoglycemia should be kept in mind in patients developing symptoms like fatigue, restlessness, and sweating while on rituximab therapy

SUSY QCD impact on top-pair production associated with a Z0Z^0-boson at a photon-photon collider

The top-pair production in association with a $Z^0$-boson at a photon-photon collider is an important process in probing the coupling between top-quarks and vector boson and discovering the signature of possible new physics. We describe the impact of the complete supersymmetric QCD(SQCD) next-to-leading order(NLO) radiative corrections on this process at a polarized or unpolarized photon collider, and make a comparison between the effects of the SQCD and the standard model(SM) QCD. We investigate the dependence of the lowest-order(LO) and QCD NLO corrected cross sections in both the SM and minimal supersymmetric standard model(MSSM) on colliding energy $\sqrt{s}$ in different polarized photon collision modes. The LO, SM NLO and SQCD NLO corrected distributions of the invariant mass of $t\bar t$-pair and the transverse momenta of final $Z^0$-boson are presented. Our numerical results show that the pure SQCD effects in \ggttz process can be more significant in the $+ +$ polarized photon collision mode than in other collision modes, and the relative SQCD radiative correction in unpolarized photon collision mode varies from 32.09% to $-1.89$ when $\sqrt{s}$ goes up from $500 GeV$ to $1.5 TeV$.Comment: 22 pages and 13 figure

Experimental evaluation of a new approach for a two-stage hydrothermal biomass liquefaction process

A new approach for biomass liquefaction was developed and evaluated in a joint research project. Focus of the project, called FEBio@H2O, lies on a two-step hydrothermal conversion. Within step 1, the input biomass is converted employing a hydrothermal degradation without added catalyst or by homogeneous catalysis. Within step 2, the hydrogen accepting products of step 1, e.g., levulinic acid (LA) are upgraded by a heterogeneously catalyzed hydrogenation with hydrogen donor substances, e.g., formic acid (FA). As a result, components with an even lower oxygen content in comparison to step 1 products are formed; as an example, γ-valerolactone (GVL) can be named. Therefore, the products are more stable and contained less oxygen as requested for a possible application as liquid fuel. As a hydrothermal process, FEBio@H2O is especially suitable for highly water-containing feedstock. The evaluation involves hydrothermal conversion tests with model substances, degradation of real biomasses, transfer hydrogenation or hydrogenation with hydrogen donor of model substances and real products of step 1, catalyst selection and further development, investigation of the influence of reactor design, the experimental test of the whole process chain, and process assessment

Profiling reviewers’ social network strength and predicting the “Helpfulness” of online customer review

Online customer reviews have become a popular source of information that influences the purchasing decisions of many prospective customers. However, the rapidly increasing volume of online reviews presents a problem of information overload, which makes it difficult for customers to determine the quality of the reviews. This study defines the helpfulness of the reviews as a count variable and takes the review helpfulness prediction from both regression and classification perspectives. The influence of friends and followers on review helpfulness is examined by introducing Social Network Strength (SNS) features. Furthermore, the performance of Machine Learning (ML) algorithms and the importance of features are separately examined for both problems using different time span of reviews. The evaluation performed using a dataset of 90,671 Yelp shopping reviews demonstrates the effectiveness of the proposed approach. The findings of this study have important theoretical and practical implications for researchers, businesses, reviewers and review platforms

Sobre la mort d'Ivan Illitx

En aquest text, els professors de l'Àrea d'Humanitats de l'Escola Universitària d'Infermeria, Fisioteràpia i Nutrició Blanquerna de la Universitat Ramon Llull, analitzen críticament una de les obres menors de Lleó Tolstoi, La mort d'Ivan Illitx. Després de contextualitzar-la, investiguen el tema central de l'obra, l'acompanyament al ben morir i fan lúcides les reflexions sobre l'art d'afrontar la mort en el nostre present

La salut comunitària a la Roca del Vallès: informe diagnòstic per al projecte COMSalut

Salut pública; Estat de salut; PoblacióSalud pública; Estado de salud; PoblaciónPublic health; Health condition; PopulationAquest informe vol analitzar l’estat de salut de la població del municipi de la Roca del Vallès per detectar les principals necessitats i possibilitats de millora en termes de salut des de l’acció dels agents territorials dins el marc del projecte COMSalut. Segons la metodologia de participació comunitària, COMSalut preveu un estudi sistemàtic quantitatiu dels registres d’informació sanitària i demogràfica existents per obtenir els indicadors que es consideren rellevants per al coneixement de l’estat de salut d’una comunitat. També preveu un estudi qualitatiu, amb participació comunitària, dels professionals i dels habitants del municipi, per poder detectar els actius i identificar les necessitats en salut. Finalment, inclou la priorització d’aquestes necessitats de cara a la planificació i a la realització d’accions de millora. Aquesta priorització també es du a terme amb la participació de la comunitat

A review of different deep learning techniques for sperm fertility prediction

Sperm morphology analysis (SMA) is a significant factor in diagnosing male infertility. Therefore, healthy sperm detection is of great significance in this process. However, the traditional manual microscopic sperm detection methods have the disadvantages of a long detection cycle, low detection accuracy in large orders, and very complex fertility prediction. Therefore, it is meaningful to apply computer image analysis technology to the field of fertility prediction. Computer image analysis can give high precision and high efficiency in detecting sperm cells. In this article, first, we analyze the existing sperm detection techniques in chronological order, from traditional image processing and machine learning to deep learning methods in segmentation and classification. Then, we analyze and summarize these existing methods and introduce some potential methods, including visual transformers. Finally, the future development direction and challenges of sperm cell detection are discussed. We have summarized 44 related technical papers from 2012 to the present. This review will help researchers have a more comprehensive understanding of the development process, research status, and future trends in the field of fertility prediction and provide a reference for researchers in other fields