Geochemistry in the modern soil survey program

Elemental analysis has played an important role in the characterization of soils since inception of the soil survey in the US. Recent efforts in analysis of trace and major elements (geochemistry) have provided necessary data to soil survey users in a variety of areas. The first part of this paper provides a brief overview of elemental sources, forms, mobility, and bioavailability; critical aspects important to users of soil survey geochemical data for appropriate use and interpretations. Examples are provided based on data gathered as part of the US soil survey program. The second part addresses the organization of sample collection in soil survey and how soil surveys are ideally suited as a sampling strategy for soil geochemical studies. Geochemistry is functional in characterization of soil types, determining soil processes, ecological evaluation, or issues related to soil quality and health, such as evaluating suitability of soils for urban or agricultural land use. Applications of geochemistry are on-going across the US and are documented herein. This analytical direction of soil survey complements historic efforts of the National Cooperative Soil Survey Program and addresses the increasing need of soil survey users for data that assists in understanding the influence of human activities on soil properties

Rapid identification of BCR/ABL1-like acute lymphoblastic leukaemia patients using a predictive statistical model based on quantitative real time-polymerase chain reaction: clinical, prognostic and therapeutic implications.

BCR/ABL1-like acute lymphoblastic leukaemia (ALL) is a subgroup of B-lineage acute lymphoblastic leukaemia that occurs within cases without recurrent molecular rearrangements. Gene expression profiling (GEP) can identify these cases but it is expensive and not widely available. Using GEP, we identified 10 genes specifically overexpressed by BCR/ABL1-like ALL cases and used their expression values - assessed by quantitative real time-polymerase chain reaction (Q-RT-PCR) in 26 BCR/ABL1-like and 26 non-BCR/ABL1-like cases to build a statistical "BCR/ABL1-like predictor", for the identification of BCR/ABL1-like cases. By screening 142 B-lineage ALL patients with the "BCR/ABL1-like predictor", we identified 28/142 BCR/ABL1-like patients (19·7%). Overall, BCR/ABL1-like cases were enriched in JAK/STAT mutations (P < 0·001), IKZF1 deletions (P < 0·001) and rearrangements involving cytokine receptors and tyrosine kinases (P = 0·001), thus corroborating the validity of the prediction. Clinically, the BCR/ABL1-like cases identified by the BCR/ABL1-like predictor achieved a lower rate of complete remission (P = 0·014) and a worse event-free survival (P = 0·0009) compared to non-BCR/ABL1-like ALL. Consistently, primary cells from BCR/ABL1-like cases responded in vitro to ponatinib. We propose a simple tool based on Q-RT-PCR and a statistical model that is capable of easily, quickly and reliably identifying BCR/ABL1-like ALL cases at diagnosis

Tailoring CD19xCD3-DART exposure enhances T-cells to eradication of B-cell neoplasms.

Many patients with B-cell malignancies can be successfully treated, although tumor eradication is rarely achieved. T-cell-directed killing of tumor cells using engineered T-cells or bispecific antibodies is a promising approach for the treatment of hematologic malignancies. We investigated the efficacy of CD19xCD3 DART bispecific antibody in a broad panel of human primary B-cell malignancies. The CD19xCD3 DART identified 2 distinct subsets of patients, in which the neoplastic lymphocytes were eliminated with rapid or slow kinetics. Delayed responses were always overcome by a prolonged or repeated DART exposure. Both CD4 and CD8 effector cytotoxic cells were generated, and DART-mediated killing of CD4+ cells into cytotoxic effectors required the presence of CD8+ cells. Serial exposures to DART led to the exponential expansion of CD4 + and CD8 + cells and to the sequential ablation of neoplastic cells in absence of a PD-L1-mediated exhaustion. Lastly, patient-derived neoplastic B-cells (B-Acute Lymphoblast Leukemia and Diffuse Large B Cell Lymphoma) could be proficiently eradicated in a xenograft mouse model by DART-armed cytokine induced killer (CIK) cells. Collectively, patient tailored DART exposures can result in the effective elimination of CD19 positive leukemia and B-cell lymphoma and the association of bispecific antibodies with unmatched CIK cells represents an effective modality for the treatment of CD19 positive leukemia/lymphoma

HOMOGENIZATION METHOD FOR 2-D NANOSTRUCTURE REINFORCED EPOXY

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A robust and validated integrated prognostic index for defining risk groups in adult acute lymphoblastic leukemia: an EWALL collaborative study

\ua9 2024 by The American Society of Hematology.Risk stratification is crucial to the successful treatment of acute lymphoblastic leukemia (ALL). Although numerous risk factors have been identified, an optimal prognostic model for integrating variables has not been developed. We used individual patient data from 4 contemporary academic national clinical trials, UKALL14, NILG-ALL10/07, GIMEMALAL1913, and PETHEMA-ALL-HR2011, to generate and validate the European Working Group for Adult ALL prognostic index (EWALL-PI), which is based on white blood cell count, genetics, and end of induction minimal residual disease (MRD). Individual patient risk scores were calculated for 778 patients aged 15 to 67 years in complete remission using the validated UKALL-PI formula, applying minor modifications to reflect differences between pediatric and adult ALL. Per-trial analysis revealed that EWALL-PI correlated with relapse and death. Regression analysis revealed that each unit increase in EWALL-PI increased the risk of relapse or death by ~30% with no evidence of heterogeneity across trials or patient subgroups. EWALL-PI–defined risk models outperformed the stratification algorithms used by each trial. Threshold analysis revealed an EWALL-PI threshold that divided patients with B cell and T cell into standard (EWALL-PI &lt;2.50) and high (EWALL-PI ≥2.50) risk groups, respectively. Per-trial analysis showed that patients at high risk had a significantly increased relapse rate and inferior survival compared with patients with standard risk (subdistribution hazard ratio for relapse, ranged from 1.85 to 3.28; hazard ratio for death, 1.73 to 3.03). Subgroup analysis confirmed the robustness of these risk groups by sex, age, white blood cell count, and lineage. In conclusion, we validated an integrated risk model across 4 independent adult ALL clinical trials, demonstrating its utility defining clinically relevant risk groups

La colecistectomia laparoscopica a “bassa pressione” nei pazienti ad alto rischio (ASA III e IV) nella nostra esperienza

The insufflation pressure used for laparoscopic cholecystectomy is usually 12-15 mm Hg, and a pneumoperitoneum with carbon dioxide has a significant effect on both cardiovascular and respiratory function. These effects are transient in young, healthy patients, but may be dangerous in ASA III and IV patients with a poor cardiac reserve. This study was designed to assess the feasibility of performing laparoscopic cholecystectomy at 6.5-8 mm Hg insufflation pressure in "high-risk" patients. Thirteen patients, 10 ASA III and 3 ASA IV, with cholelithiasis, were included in this study The insufflation pressure was 6.5-8 mm Hg, with a 10 degrees anti-Trendelenburg position. The cardiovascular and blood gas variables studied were: mean arterial blood pressure, heart rate, respiratory rate, and end-tidal CO2 pressure. The authors reported no conversions and no intra- or postoperative complications. During insufflation heart rate and mean arterial blood pressure increased minimally if compared with laparoscopic cholecystectomy at 12-15 mm Hg. Pa CO2 increased after insufflation (+5 mm Hg), and the end-tidal CO2 pressure gradient was moderate (3.5 mm Hg) and unchanged during surgery. A low-pressure pneumoperitoneum is feasible for laparoscopic cholecystectomy and minimizes the adverse haemodynamic effects of peritoneal insufflation

A prospective multicentre study evaluating the outcomes of the abdominal wall dehiscence repair using posterior component separation with transversus abdominis muscle release reinforced by a retro-muscular mesh: filling a step

Background This study aimed to evaluate the results of posterior component separation (CS) and transversus abdominis muscle release (TAR) with retro-muscular mesh reinforcement in patients with primary abdominal wall dehiscence (AWD). The secondary aims were to detect the incidence of postoperative surgical site occurrence and risk factors of incisional hernia (IH) development following AWD repair with posterior CS with TAR reinforced by retromuscular mesh. Methods Between June 2014 and April 2018, 202 patients with grade IA primary AWD (Björck’s first classification) following midline laparotomies were treated using posterior CS with TAR release reinforced by a retro-muscular mesh in a prospective multicenter cohort study. Results The mean age was 42 ± 10 years, with female predominance (59.9%). The mean time from index surgery (midline laparotomy) to primary AWD was 7 ± 3 days. The mean vertical length of primary AWD was 16 ± 2 cm. The median time from primary AWD occurrence to posterior CS + TAR surgery was 3 ± 1 days. The mean operative time of posterior CS + TAR was 95 ± 12 min. No recurrent AWD occurred. Surgical site infections (SSI), seroma, hematoma, IH, and infected mesh occurred in 7.9%, 12.4%, 2%, 8.9%, and 3%, respectively. Mortality was reported in 2.5%. Old age, male gender, smoking, albumin level &lt; 3.5 gm%, time from AWD to posterior CS + TAR surgery, SSI, ileus, and infected mesh were significantly higher in IH. IH rate was 0.5% and 8.9% at two and three years, respectively. In multivariate logistic regression analyses, the predictors of IH were time from AWD till posterior CS + TAR surgical intervention, ileus, SSI, and infected mesh. Conclusion Posterior CS with TAR reinforced by retro-muscular mesh insertion resulted in no AWD recurrence, low IH rates, and low mortality of 2.5%. Trial registration Clinical trial: NCT05278117

Philadelphia-like acute lymphoblastic leukemia is associated with minimal residual disease persistence and poor outcome. First report of the minimal residual disease-oriented GIMEMA LAL1913

Early recognition of Philadelphia-like (Ph-like) acute lymphoblastic leukemia (ALL) cases could impact on the management and outcome of this subset of B-lineage ALL. In order to assess the prognostic value of the Ph-like status in a pediatric-inspired, minimal residual disease (MRD)driven trial, we screened 88 B-lineage ALL cases negative for major fusion genes (BCR-ABL1, ETV6-RUNX1, TCF3-PBX1 and KTM2Ar) enrolled in the GIMEMA LAL1913 front-line protocol for adult BCR/ABL1-negative ALL. The screening - performed using the “BCR/ABL1-like predictor” - identified 28 Ph-like cases (31.8%), characterized by CRLF2 overexpression (35.7%), JAK/STAT pathway mutations (33.3%), IKZF1 (63.6%), BTG1 (50%) and EBF1 (27.3%) deletions, and rearrangements targeting tyrosine kinases or CRLF2 (40%). The correlation with outcome highlighted that: i) the complete remission rate was significantly lower in Ph-like compared to non-Ph-like cases (74.1% vs. 91.5%, P=0.044); ii) at time point 2, decisional for transplant allocation, 52.9% of Ph-like cases versus 20% of non-Ph-like were MRD-positive (P=0.025); iii) the Ph-like profile was the only parameter associated with a higher risk of being MRD-positive at time point 2 (P=0.014); iv) at 24 months, Ph-like patients had a significantly inferior event-free and disease-free survival compared to non-Ph-like patients (33.5% vs. 66.2%, P=0.005 and 45.5% vs. 72.3%, P=0.062, respectively). This study documents that Ph-like patients have a lower complete remission rate, event-free survival and disease-free survival, as well as a greater MRD persistence also in a pediatric-oriented and MRD-driven adult ALL protocol, thus reinforcing that the early recognition of Ph-like ALL patients at diagnosis is crucial to refine risk-stratification and to optimize therapeutic strategies

Importance of data structure in comparing two dimension reduction methods for classification of microarray gene expression data

BACKGROUND: With the advance of microarray technology, several methods for gene classification and prognosis have been already designed. However, under various denominations, some of these methods have similar approaches. This study evaluates the influence of gene expression variance structure on the performance of methods that describe the relationship between gene expression levels and a given phenotype through projection of data onto discriminant axes. RESULTS: We compared Between-Group Analysis and Discriminant Analysis (with prior dimension reduction through Partial Least Squares or Principal Components Analysis). A geometric approach showed that these two methods are strongly related, but differ in the way they handle data structure. Yet, data structure helps understanding the predictive efficiency of these methods. Three main structure situations may be identified. When the clusters of points are clearly split, both methods perform equally well. When the clusters superpose, both methods fail to give interesting predictions. In intermediate situations, the configuration of the clusters of points has to be handled by the projection to improve prediction. For this, we recommend Discriminant Analysis. Besides, an innovative way of simulation generated the three main structures by modelling different partitions of the whole variance into within-group and between-group variances. These simulated datasets were used in complement to some well-known public datasets to investigate the methods behaviour in a large diversity of structure situations. To examine the structure of a dataset before analysis and preselect an a priori appropriate method for its analysis, we proposed a two-graph preliminary visualization tool: plotting patients on the Between-Group Analysis discriminant axis (x-axis) and on the first and the second within-group Principal Components Analysis component (y-axis), respectively. CONCLUSION: Discriminant Analysis outperformed Between-Group Analysis because it allows for the dataset structure. An a priori knowledge of that structure may guide the choice of the analysis method. Simulated datasets with known properties are valuable to assess and compare the performance of analysis methods, then implementation on real datasets checks and validates the results. Thus, we warn against the use of unchallenging datasets for method comparison, such as the Golub dataset, because their structure is such that any method would be efficient