The Prospect of Recovering Vanadium, Nickel, and Molybdenum from Stone Coal by Using Combined Beneficiation and Metallurgy Technology Based on Mineralogy Features

Black shale ore contains rich strategic metal resources such as vanadium, nickel, and molybdenum, but due to its complex composition, it is currently only used in the vanadium extraction industry. Metals such as nickel and molybdenum have not been effectively recovered, resulting in environmental pollution and resource waste. Using mineralogical features and a combination of beneficiation and metallurgy-based tests, the present work carried out feasibility studies of the combined beneficiation and metallurgy processes. The mineralogical features of the stone coal sample were studied using chemical analysis, an automatic mineral analyzer (BPMA), etc., and we identified the main phase composition, embedded characteristics, and particle size distribution of the associated strategic metals, vanadium, nickel, and molybdenum. The results showed that the grade of V2O5 in the stone coal was 1.29%, which was mainly present in carbonaceous clay and mica minerals. The nickel grade was 0.53%, mainly in the form of nickel–magnesium spinel and a small amount of nickel-containing magnesite. The stone coal contained 0.11% molybdenum; the mineral particles were fine, mostly in the form of molybdenite, and some were associated with carbonaceous matter and carbonaceous clay minerals. Based on the mineralogical feature, we proposed using the scrubbing–desliming and flotation process to enrich vanadium, nickel, and molybdenum. Our preliminary experiments obtained two products: vanadium–molybdenum-rich sludge and nickel-containing tailings. The V2O5 and molybdenum grades in the sludge were 4.10% and 0.44%, respectively, and the recovery was 41.31% and 51.40%, respectively. The nickel grade in the tailings was 1.49%. These products were roasted and leached. The vanadium, nickel, and molybdenum in the stone coal were effectively recovered through the beneficiation–metallurgy combination process, and the comprehensive utilization rate of the stone coal was improved

Direct evidence of cheetah (Acinonyx jubatus) as intermediate host of Toxoplasma gondii through isolation of viable strains

Abstract Toxoplasma gondii causes lifelong infection in most definitive and intermediate hosts. Clinical cases of toxoplasmosis in captive cheetahs have been reported. However, there are few reports of viable T. gondii strains isolated from cheetahs. Here, T. gondii infection was investigated using molecular and serological assays in cheetahs from China. Modified agglutination test (MAT) (cut-off: 1:25) indicated that all six examined cheetahs (n = 6) showed T. gondii antibodies. Toxoplasma gondii DNA was detected in three out of five cheetahs. Two viable T. gondii strains were isolated from the striated muscles of two cheetahs using mice bioassay. They were designated as TgCheetahCHn1 and TgCheetahCHn2. Genetic characterization of DNA derived from tachyzoites was performed using RFLP-PCR of 10 markers. Toxoplasma gondii TgCheetahCHn1 is ToxoDB PCR-RFLP genotype #319, and the alleles of ROP18/ROP5 types were 3/7. TgCheetahCHn2 is ToxoDB genotype #9, and the alleles of ROP18/ROP5 were 3/6. The average survival time of TgCheetahCHn1-infected Swiss mice was 22 ± 1 days (n = 23), and the mice did not have detectable T. gondii-specific antibodies until 117 ± 30 days post-inoculation (n = 8), therefore, TgCheetahCHn1 had intermediate virulence. TgCheetahCHn2 was avirulent for Swiss mice. Few brain tissue cysts (0–50) were observed in the mice inoculated with TgCheetahCHn1 or TgCheetahCHn2. The results provide direct evidence of cheetah as intermediate host of T. gondii

Isolation and Genetic Characterization of <i>Toxoplasma gondii</i> from a Patas Monkey (<i>Erythrocebus patas</i>) in China

Many cases of Toxoplasma gondii infection have been reported worldwide in non-human primates (NHPs), especially in captive New World monkeys. However, few studies on toxoplasmosis in Old World monkeys have been conducted. In this study, serological and molecular biological analyses were carried out to look for T. gondii antibodies and T. gondii infection in 13 NHPs from China. T. gondii infection was confirmed in 8 NHP cases. T. gondii antibodies were detected in 1/5 New World monkeys and in 4/7 Old World monkeys. T. gondii DNA was detected in 3/5 New World monkeys and 5/7 Old World monkeys. The one ring-tailed lemur was negative for both antibodies and DNA of T. gondii. The most common clinical manifestations of T. gondii infection were malaise, poor appetite, emaciation, and foamy nasal discharge. The most common histopathological findings were interstitial pneumonia, necrotic hepatitis, necrotizing myocarditis, lymphadenitis, and necrotic splenitis. One viable T. gondii strain was successfully isolated from the myocardium of a patas monkey (Erythrocebus patas) by bioassay in mice. T. gondii tachyzoites were obtained from cell cultures and were designated as TgMonkeyCHn2. The genotype of this strain belongs to ToxoDB genotype #9, and the allele of ROP18/ROP5 gene was 3/6. TgMonkeyCHn2 tachyzoites were avirulent in Swiss mice. To our knowledge, this is the first report of fatal toxoplasmosis in a patas monkey. T. gondii infection in patas monkeys may indicate environmental contamination by oocysts. The patas monkey is a new host record for T. gondii

Additional file 1 of Direct evidence of cheetah (Acinonyx jubatus) as intermediate host of Toxoplasma gondii through isolation of viable strains

Supplementary Material

Survival outcomes after breast-conserving therapy compared with mastectomy for patients with early-stage metaplastic breast cancer: a population-based study of 2412 patients

Background: Previous studies revealed that patients with early-stage metaplastic breast cancer (MBC) underwent mastectomy more often than breast-conserving therapy (BCT) mainly due to the larger tumor size. This study was performed to compare the survival outcomes following BCT versus mastectomy for patients with early-stage MBC. Methods: Surveillance, Epidemiology, and End Results (SEER) database was used to identify women diagnosed with early-stage MBC (T1-3N0-3M0) between 2001 and 2016, who were treated with either BCT or mastectomy. We assessed overall survival (OS) and breast cancer-specific survival (BCSS) using the Kaplan-Meier method and hazard ratios using Cox proportional hazards models. Results: A total of 2412 MBC patients were identified, 881 (36.5%) of whom underwent BCT and 1531(63.5%) underwent mastectomy. The median follow-up time was 73 months. Most of patients had older age (≥50 years old), larger tumor size, higher American Joint Committee on Cancer (AJCC) stage and hormone receptor negativity. After adjustment for confounding variables, patients who underwent BCT had significantly improved OS (5-year OS: 84.3% vs 62.5%; 10-year OS: 73.0% vs 52.1%; adjusted HR = 0.76, 95%CI: 0.59–0.97, p = 0.028) and BCSS (5-year BCSS: 89.1% vs 70.8%; 10-year BCSS: 83.9% vs 67.5%; adjusted HR = 0.72, 95%CI: 0.53–0.96, p = 0.026) than those who underwent mastectomy, and this improvement remained significant for all T and N stages of MBC except for N2-3 stage. Conclusion: BCT conferred improved OS and BCSS compared with mastectomy for patients with early-stage MBC, and the improvement persisted in almost all of the subgroups of different T and N stages

Longitudinal MRI-based fusion novel model predicts pathological complete response in breast cancer treated with neoadjuvant chemotherapy: a multicenter, retrospective studyResearch in context

Summary: Background: Accurate identification of pCR to neoadjuvant chemotherapy (NAC) is essential for determining appropriate surgery strategy and guiding resection extent in breast cancer. However, a non-invasive tool to predict pCR accurately is lacking. Our study aims to develop ensemble learning models using longitudinal multiparametric MRI to predict pCR in breast cancer. Methods: From July 2015 to December 2021, we collected pre-NAC and post-NAC multiparametric MRI sequences per patient. We then extracted 14,676 radiomics and 4096 deep learning features and calculated additional delta-value features. In the primary cohort (n = 409), the inter-class correlation coefficient test, U-test, Boruta and the least absolute shrinkage and selection operator regression were used to select the most significant features for each subtype of breast cancer. Five machine learning classifiers were then developed to predict pCR accurately for each subtype. The ensemble learning strategy was used to integrate the single-modality models. The diagnostic performances of models were evaluated in the three external cohorts (n = 343, 170 and 340, respectively). Findings: A total of 1262 patients with breast cancer from four centers were enrolled in this study, and pCR rates were 10.6% (52/491), 54.3% (323/595) and 37.5% (66/176) in HR+/HER2−, HER2+ and TNBC subtype, respectively. Finally, 20, 15 and 13 features were selected to construct the machine learning models in HR+/HER2−, HER2+ and TNBC subtypes, respectively. The multi-Layer Perception (MLP) yields the best diagnostic performances in all subtypes. For the three subtypes, the stacking model integrating pre-, post- and delta-models yielded the highest AUCs of 0.959, 0.974 and 0.958 in the primary cohort, and AUCs of 0.882–0.908, 0.896–0.929 and 0.837–0.901 in the external validation cohorts, respectively. The stacking model had accuracies of 85.0%–88.9%, sensitivities of 80.0%–86.3%, and specificities of 87.4%–91.5% in the external validation cohorts. Interpretation: Our study established a novel tool to predict the responses of breast cancer to NAC and achieve excellent performance. The models could help to determine post-NAC surgery strategy for breast cancer. Funding: This study is supported by grants from the National Natural Science Foundation of China (82171898, 82103093), the Deng Feng project of high-level hospital construction (DFJHBF202109), the Guangdong Basic and Applied Basic Research Foundation (grant number, 2020A1515010346, 2022A1515012277), the Science and Technology Planning Project of Guangzhou City (202002030236), the Beijing Medical Award Foundation (YXJL-2020-0941-0758), and the Beijing Science and Technology Innovation Medical Development Foundation (KC2022-ZZ-0091-5). Funding sources were not involved in the study design, data collection, analysis and interpretation, writing of the report, or decision to submit the article for publication

DAGM: A novel modelling framework to assess the risk of HER2-negative breast cancer based on germline rare coding mutations

Background: Breast cancers can be divided into HER2-negative and HER2-positive subtypes according to different status of HER2 gene. Despite extensive studies connecting germline mutations with possible risk of HER2-negative breast cancer, the main category of breast cancer, it remains challenging to obtain accurate risk assessment and to understand the potential underlying mechanisms. Methods: We developed a novel framework named Damage Assessment of Genomic Mutations (DAGM), which projects rare coding mutations and gene expressions into Activity Profiles of Signalling Pathways (APSPs). Findings: We characterized and validated DAGM framework at multiple levels. Based on an input of germline rare coding mutations, we obtained the corresponding APSP spectrum to calculate the APSP risk score, which was capable of distinguish HER2-negative from HER2-positive cases. These findings were validated using breast cancer data from TCGA (AUC = 0.7). DAGM revealed that HER2 signalling pathway was up-regulated in germline of HER2-negative patients, and those with high APSP risk scores had exhibited immune suppression. These findings were validated using RNA sequencing, phosphoproteome analysis, and CyTOF. Moreover, using germline mutations, DAGM could evaluate the risk for HER2-negative breast cancer, not only in women carrying BRCA1/2 mutations, but also in those without known disease-associated mutations. Interpretation: The DAGM can facilitate the screening of subjects at high risk of HER2-negative breast cancer for primary prevention. This study also provides new insights into the potential mechanisms of developing HER2-negative breast cancer. The DAGM has the potential to be applied in the prevention, diagnosis, and treatment of HER2-negative breast cancer. Funding: This work was supported by the National Key Research and Development Program of China (grant no. 2018YFC0910406 and 2018AAA0103302 to CZ); the National Natural Science Foundation of China (grant no. 81202076 and 82072939 to MY, 81871513 to KW); the Guangzhou Science and Technology Program key projects (grant no. 2014J2200007 to MY, 202002030236 to KW); the National Key R&D Program of China (grant no. 2017YFC1309100 to CL); Shenzhen Science and Technology Planning Project (grant no. JCYJ20170817095211560 574 to YN); and the Natural Science Foundation of Guangdong Province (grant no. 2017A030313882 to KW and S2013010012048 to MY); Hefei National Laboratory for Physical Sciences at the Microscale (grant no. KF2020009 to GN); and RGC General Research Fund (grant no. 17114519 to YQS)