Model and Evaluation: Towards Fairness in Multilingual Text Classification

Recently, more and more research has focused on addressing bias in text classification models. However, existing research mainly focuses on the fairness of monolingual text classification models, and research on fairness for multilingual text classification is still very limited. In this paper, we focus on the task of multilingual text classification and propose a debiasing framework for multilingual text classification based on contrastive learning. Our proposed method does not rely on any external language resources and can be extended to any other languages. The model contains four modules: multilingual text representation module, language fusion module, text debiasing module, and text classification module. The multilingual text representation module uses a multilingual pre-trained language model to represent the text, the language fusion module makes the semantic spaces of different languages tend to be consistent through contrastive learning, and the text debiasing module uses contrastive learning to make the model unable to identify sensitive attributes' information. The text classification module completes the basic tasks of multilingual text classification. In addition, the existing research on the fairness of multilingual text classification is relatively simple in the evaluation mode. The evaluation method of fairness is the same as the monolingual equality difference evaluation method, that is, the evaluation is performed on a single language. We propose a multi-dimensional fairness evaluation framework for multilingual text classification, which evaluates the model's monolingual equality difference, multilingual equality difference, multilingual equality performance difference, and destructiveness of the fairness strategy. We hope that our work can provide a more general debiasing method and a more comprehensive evaluation framework for multilingual text fairness tasks

Circulating tumor DNA determining hyperprogressive disease after CAR-T therapy alarms in DLBCL: a case report and literature review

Chimeric antigen receptor T-cell therapy (CAR-T) has been widely applied in the clinical practice of relapse/refractory (R/R) diffuse large B-cell lymphoma (DLBCL) due to its promising effects. Hyperprogressive disease (HPD) has gained attention for rapid tumor progression and has become a therapeutic and prognostic challenge. Here, we present a patient who had suffered from several recurrences previously and controlled well with a very small tumor lesion left was infused with CD19/CD22 bispecific CAR-T, with no immune effector cell-associated neurotoxicity syndrome, or cytokine release syndrome observed. However, rapid deterioration, subsequent imaging examination, circulating tumor DNA, and serum biomarkers detection identified HPD. The patient did not respond to salvage treatment and died 40 days after infusion. To our knowledge, only one case of HPD in DLBCL after CAR-T therapy has been reported. This fatal case alarmed the risk of HPD and the ctDNA profile monitoring we used was performed as a non-invasive method to diagnose HPD, providing far-reaching practical instruction for CAR-T therapy

Atomic structure of Mg-based metallic glasses from molecular dynamics and neutron diffraction

We use a combination of classical molecular dynamics simulation and neutron diffraction to identify the atomic structure of five different Mg–Zn–Ca bulk metallic glasses, covering a range of compositions with substantially different behaviour when implanted in vitro. There is very good agreement between the structures obtained from computer simulation and those found experimentally. Bond lengths and the total correlation function do not change significantly with composition. The zinc and calcium bonding shows differences between composition: the distribution of Zn–Ca bond lengths becomes narrower with increasing Zn content, and the preference for Zn and Ca to avoid bonding to themselves or each other becomes less strong, and, for Zn–Ca, transforms into a positive preference to bond to each other. This transition occurs at about the same Zn content at which the behaviour on implantation changes, hinting at a possible structural connection. A very broad distribution of Voronoi polyhedra are also found, and this distribution broadens with increasing Zn content. The efficient cluster packing model, which is often used to describe the structure of bulk metallic glasses, was found not to describe these systems well