Assessing soil remediation effect of Cr and Pb based on bioavailability using DGT, BCR and standardized determination method.

In the field of soil remediation, the importance of bioavailability of pollutants has not received adequate attention, leading to the excessive application of remediation measures. Therefore, to ensure the safe use of farmland soil, a scientific method is needed to assess labile contaminants and their translocation in plants. To evaluate soil remediation effect based on bioavailability, the concentrations of these heavy metals in soil were analyzed using by the method for total metal content, the Community Bureau of Reference (BCR) extraction, and the diffusive gradients in thin films (DGT) technique. The results reveal that the correlation coefficients between metal concentrations measured by DGT and those accumulated in rice grains are the highest (Cr-R2 = 0.8966, Pb-R2 = 0.9045). However, the capability of method for total metal content to evaluate the remediation effect of heavy metals is very limited. In contrast, although Cr and Pb measured by BCR show a high correlation with HMs in rice plants, the method still falls short in precisely assessing bioavailability. Significantly, DGT proves to be more effective, successfully distinguishing the remediation effects of different treatments. Generally, DGT offers a more accurate and simpler assessment method, underscoring its practical significance for monitoring soil remediation and environmental management.

Multi-Label Local to Global Learning: A Novel Learning Paradigm for Chest X-Ray Abnormality Classification.

Deep neural network (DNN) approaches have shown remarkable progress in automatic Chest X-rays classification. However, existing methods use a training scheme that simultaneously trains all abnormalities without considering their learning priority. Inspired by the clinical practice of radiologists progressively recognizing more abnormalities and the observation that existing curriculum learning (CL) methods based on image difficulty may not be suitable for disease diagnosis, we propose a novel CL paradigm, named multi-label local to global (ML-LGL). This approach iteratively trains DNN models on gradually increasing abnormalities within the dataset, i,e, from fewer abnormalities (local) to more ones (global). At each iteration, we first build the local category by adding high-priority abnormalities for training, and the abnormality's priority is determined by our three proposed clinical knowledge-leveraged selection functions. Then, images containing abnormalities in the local category are gathered to form a new training set. The model is lastly trained on this set using a dynamic loss. Additionally, we demonstrate the superiority of ML-LGL from the perspective of the model's initial stability during training. Experimental results on three open-source datasets, PLCO, ChestX-ray14 and CheXpert show that our proposed learning paradigm outperforms baselines and achieves comparable results to state-of-the-art methods. The improved performance promises potential applications in multi-label Chest X-ray classification.

[Clinical study on treating insulin resistance and promoting ovulation in polycystic ovary syndrome].

OBJECTIVE: To investigate the effects of metformin and clomiphene on infertility caused by polycystic ovary syndrome (PCOS) with insulin-resistance (IR) and to observe the effects of metformin on PCOS with pseudoacanthosis nigricans (AN) and IR. METHODS: Seventy infertility patients caused by PCOS with IR were randomly divided into three groups : patients in group Aa (n = 20) took metformin 500 mg only, three times daily for 3 months; patients in group Ab (n = 20) took clomiphene 50 mg only, once daily from the 5th day of menstrual cycle or withdrawal bleeding for 5 days and 3 cycles, and patients in group Ac (n = 30) were treated by metformin and clomiphene for 3 cycles, with the same dosages as groups Aa and Ab. Thirty patients who suffered from PCOS with AN and IR were served as group B, They took metformin only, the same as group Aa. The following indexes were measured before and after three months or cycles of treatment in all the patients: body height, weight, waistline, hipline, body mass index (BMI), waist hip ratio (WHR), fasting insulin (FINS), fasting blood-glucose (FBG), total cholesterol (TC), triglyceride (TG), and sex hormones [follicle-stimulating hormone (FSH), luteotropic hormone (LH), prolactin (PRL), estradiol (E(2)), progestin (P), testosterone (T)]. RESULTS: The pregnant rate was 15% (group Aa), 20% (group Ab), and 57% (group Ac) respectively. It was significantly higher in group Ac than in groups Aa and Ab, (P < 0.01), while there was no significant difference between the latter two groups (P > 0.05). In group Ac the pretreatment levels of FINS, BMI, T, TG, and TC were (49.7 +/- 6.4) mU/L, 29.4 +/- 2.2, (6.4 +/- 2.2) nmol/L, (4.1 +/- 1.0) mmol/L, (6.3 +/- 0.5) mmol/L, and posttreatment levels were (27.7 +/- 1.8) mU/L, 23.6 +/- 5.2, (3.8 +/- 2.0) nmol/L, (2.2 +/- 0.7) mmol/L, (4.6 +/- 0.5) mmol/L. In group Aa pretreatment levels of FINS, BMI, T, TG, and TC were (50.0 +/- 8.2) mU/L, 28.7 +/- 1.2, (6.4 +/- 2.0) nmol/L, (4.3 +/- 1.2) mmol/L, (6.6 +/- 0.3) mmol/L, and posttreatment levels were (29.9 +/- 8.2) mU/L, 22.4 +/- 9.3, (4.3 +/- 0.9) nmol/L, (2.3 +/- 0.3) mmol/L, (4.8 +/- 0.6) mmol/L. In group B pretreatment levels of FINS, BMI, T, TG, and TC were (51.0 +/- 8.1) mU/L, 29.8 +/- 3.1, (6.3 +/- 3.5) nmol/L, (4.5 +/- 1.2) mmol/L, (6.8 +/- 0.2) mmol/L, and posttreatment levels were (28.5 +/- 2.8) mU/L, 23.4 +/- 6.1, (3.0 +/- 0.9) nmol/L, (2.3 +/- 0.9) mmol/L, (5.0 +/- 0.6) mmol/L. In groups Ac, Aa and B, the IR condition was obviously improved and posttreatment serum levels of T, TG, TC, FINS and BMI were significantly lower than those of pretreatment (all P < 0.01). In group Ab pretreatment levels of FINS, BMI, T, TG, and TC were (48.8 +/- 7.4) mU/L, 27.3 +/- 2.8, (6.0 +/- 2.0) nmol/L, (3.9 +/- 1.4) mmol/L, (6.4 +/- 0.6) mmol/L, and posttreatment levels were (42.9 +/- 7.0) mU/L, 27.5 +/- 3.1, (4.0 +/- 2.4) nmol/L, (3.9 +/- 0.3) mmol/L, (5.9 +/- 0.3) mmol/L, (all P > 0.05). Among patients in group B, 90% (27/30) menstrual condition and ovulation function were improved and AN was reduced in different degree after three months' treatment. CONCLUSION: Metformin can increase the sensitivity of PCOS to clomiphene and improve ovulation function of clomiphene. Metformin plus clomiphene is an effective way of treating infertility caused by PCOS with IR.