Nodule Growth Research Articles

Preparation and modification of PVDF membrane via VIPS method for membrane distillation

Membrane distillation (MD) is a promising technology for treating high-salinity mine water. However, MD membranes are known to have low membrane flux and are prone to fouling. In this study, we used the cost-effective and controllable vapor-induced phase separation (VIPS) technology to prepare polyvinylidene difluoride (PVDF) membranes, replacing the traditional immersion precipitation method and optimizing the membrane structure by including LiCl and acetone as porogen in the casting solution. The results showed that the membrane prepared using the VIPS method exhibited a highly open interconnected porous surface. Unlike traditional MD membranes with a dense epidermal layer and large finger-like pores, these optimized membranes had a symmetrical and uniform internal structure, leading to a high flux of 8.62 kg·(m2·h)−1 during direct contact membrane distillation testing. Different porogens produced varied results on the VIPS process and varying effects on membrane structure. The use of LiCl promoted the formation of PVDF β-phase, resulting in a decrease in the number of spherical nodules on the membrane surface, as well as improved density and smoothness. Consequently, this reduced fouling risk during membrane distillation while slightly decreasing membrane flux. On the other hand, acetone rapidly evaporated during the VIPS process, facilitating pre-gelatinization and α-phase formation of PVDF. This concurrent effect effectively restricted excessive nodule growth on the membrane surface, endowing the membrane with antifouling capabilities while preserving high flux.

A β-Carboline Derivate PAD4 Inhibitor Reshapes Neutrophil Phenotype and Improves the Tumor Immune Microenvironment against Triple-Negative Breast Cancer.

Triple-negative breast cancer is a highly aggressive and heterogeneous breast cancer subtype characterized by early metastasis, poor prognosis, and high recurrence. Targeting histone citrullination-mediated chromatin dysregulation to induce epigenetic alterations shows great promise in TNBC therapy. We report the synthesis, optimization, and evaluation of a novel series of β-carboline-derived peptidyl arginine deiminase 4 inhibitors that exhibited potent inhibition of TNBC cell proliferation. The most outstanding PAD4 inhibitor, compound 28, hindered the PAD4-H3cit-NET signaling pathway and inhibited the growth of solid tumors and pulmonary metastatic nodules in the 4T1 in situ mouse model. Furthermore, 28 improved the tumor immune microenvironment by reshaping neutrophil phenotype, upregulating the proportions of dendritic cells and M1 macrophages, and reducing the amount of myeloid-derived suppressor cells. In conclusion, our work offered 28 as an efficacious PAD4 inhibitor that exerts a combination of conventional chemotherapy and immune-boosting effects, which represents a potential therapy strategy for TNBC.

The Effectiveness of Plant Growth Promoting Rhizobacteria (PGPR) on the Growth of Root Nodules of Peanut Genotypes under Water Deficit Condition

The deficiency of water sources and soil fertility are obstacles to producing peanuts in dry land. One of effort to increase production on dry land is the utilization of PGPR biofertilizers. This study aimed to determine the growth of plants and root nodules of several peanut genotypes applied with PGPR, to understand the interaction between several peanut genotypes and PGPR on plant growth and root nodules, and to examine the relationship between water deficit conditions and the formation of root nodules. This experiment used a Complete Randomized Design-split split-plot design with the main plots being D0 = optimal conditions (no water deficit) and D1 = water deficit. The subplots were P0 = no PGPR and P1 = with PGPR. The sub-subplots consisted of five peanut genotypes: V1 = Hypoma-I, V2 = Domba, V3 = Talam, V4 = Bison, and V5 = G300-II. The observations showed that the addition of PGPR resulted in higher plant growth compared to those without PGPR and had more effective root nodules in nitrogen fixation compared to treatments without PGPR. The application of PGPR and genotype did not show significant interaction on plant growth and root nodules under water deficit conditions. Water deficit significantly affected all parameters of plant growth and root nodules. PGPR significantly affected the parameters of leaf number rate, nodule number, and nodule weight. Genotype significantly affected the plant height rate. The interaction of water deficit and genotype significantly affected the leaf number rate, while the interaction of water deficit and PGPR, and the interaction of PGPR and genotype did not significantly affect all observation parameters.

Numerical Simulation of Cathode Nodule Local Effects

As one of the main factors decreasing current efficiency and product quality, the growth of nodules deserves attention in the copper electrorefining process. Three-dimensional (3D) Finite Element Method models combining tertiary current distribution and fluid flow were established in this study to investigate the details of the growth of columnar nodules, including the electrolyte flow around the nodule and its effects. Compared with an inert nodule, a significant impact of the electrochemical reaction of an active nodule has been observed on the fluid flow, which may be one of the reasons for the formation of small nodule clusters on the cathode. Furthermore, the local current density is not even on the nodule surface under the comprehensive influence of local electrolyte flow, local overvoltage, and the angle with the anode surface. Thus, the head of an active nodule grows faster than the root, and the upper parts grow faster than the lower parts, leading to asymmetric growth of the nodules.

Potencial Simbiótico de Microrganismos do Solo na Promoção do Crescimento de Espécies Arbóreas da Mata Atlântica

The objective of this study was to evaluate the potential of topsoil obtained from a natural forest fragment in the Brazilian Atlantic Forest to serve as a source of symbiotic microorganisms capable of promoting the growth of native tree species in ecological restoration projects. In greenhouse conditions, 14 experiments in a completely randomized design were conducted in 1,700 cm³ pots filled with sterilized substrate. The effect of adding 80 g of topsoil, either in natura or sterilized, to the substrate was tested on the growth of 14 tree species. Plant height, stem diameter, mycorrhizal colonization and dry masses of shoot, roots, and nodules of tree species were measured. Applying the topsoil to the pots generally resulted in significant increases in height and stem diameter of seedlings compared to the control group during the four to six-month evaluation period. This effect was particularly greater in the nodulating species Plathymenia reticulata, Dalbergia nigra and Mimosa bimucronata, with increases in height and stem diameter of up to 328% and 484%, respectively. Forest topsoil also had a positive impact on the growth of shoot, roots, and nodules of the plants, significantly differing from the control groups. Only the plants that received the topsoil in natura exhibited mycorrhizal colonization and the formation of nodules in nitrogen-fixing species. These plants that established mycorrhizas and nodules presented higher concentrations of phosphorous and nitrogen in their biomass, respectively. Under controlled conditions, the use of forest topsoil proved to be a promising strategy for the introduction of microorganisms that can enhance the growth of tree species, thereby holding potential for implementation in nurseries and field settings.
 

A Growth Prediction Model of Pulmonary Ground-Glass Nodules Based on Clinical Visualization Parameters

Objective To establish a model for predicting the growth of pulmonary ground-glass nodules (GGN) based on the clinical visualization parameters extracted by the 3D reconstruction technique and to verify the prediction performance of the model. Methods A retrospective analysis was carried out for 354 cases of pulmonary GGN followed up regularly in the outpatient of pulmonary nodules in Zhoushan Hospital of Zhejiang Province from March 2015 to December 2022.The semi-automatic segmentation method of 3D Slicer was employed to extract the quantitative imaging features of nodules.According to the follow-up results,the nodules were classified into a resting group and a growing group.Furthermore,the nodules were classified into a training set and a test set by the simple random method at a ratio of 7∶3.Clinical and imaging parameters were used to establish a prediction model,and the prediction performance of the model was tested on the validation set. Results A total of 119 males and 235 females were included,with a median age of 55.0 (47.0,63.0) years and the mean follow-up of (48.4±16.3) months.There were 247 cases in the training set and 107 cases in the test set.The binary Logistic regression analysis showed that age (95%CI=1.010-1.092,P=0.015) and mass (95%CI=1.002-1.067,P=0.035) were independent predictors of nodular growth.The mass (M) of nodules was calculated according to the formula M=V×(CTmean+1000)×0.001 (where V is the volume,V=3/4πR3,R:radius).Therefore,the logit prediction model was established as ln[P/(1-P)]=-1.300+0.043×age+0.257×two-dimensional diameter+0.007×CTmean.The Hosmer-Lemeshow goodness of fit test was performed to test the fitting degree of the model for the measured data in the validation set (χ2=4.515,P=0.808).The check plot was established for the prediction model,which showed the area under receiver-operating characteristic curve being 0.702. Conclusions The results of this study indicate that patient age and nodule mass are independent risk factors for promoting the growth of pulmonary GGN.A model for predicting the growth possibility of GGN is established and evaluated,which provides a basis for the formulation of GGN management strategies.

Artificial intelligence in lung cancer screening: Detection, classification, prediction, and prognosis.

The exceptional capabilities of artificial intelligence (AI) in extracting image information and processing complex models have led to its recognition across various medical fields. With the continuous evolution of AI technologies based on deep learning, particularly the advent of convolutional neural networks (CNNs), AI presents an expanded horizon of applications in lung cancer screening, including lung segmentation, nodule detection, false-positive reduction, nodule classification, and prognosis. This review initially analyzes the current status of AI technologies. It then explores the applications of AI in lung cancer screening, including lung segmentation, nodule detection, and classification, and assesses the potential of AI in enhancing the sensitivity of nodule detection and reducing false-positive rates. Finally, it addresses the challenges and future directions of AI in lung cancer screening. AI holds substantial prospects in lung cancer screening. It demonstrates significant potential in improving nodule detection sensitivity, reducing false-positive rates, and classifying nodules, while also showing value in predicting nodule growth and pathological/genetic typing. AI offers a promising supportive approach to lung cancer screening, presenting considerable potential in enhancing nodule detection sensitivity, reducing false-positive rates, and classifying nodules. However, the universality and interpretability of AI results need further enhancement. Future research should focus on the large-scale validation of new deep learning-based algorithms and multi-center studies to improve the efficacy of AI in lung cancer screening.

Abstract 147: Identification of cell sub-populations in Neuroblastoma cell lines with single-cell-sequencing analysis

Abstract Neuroblastoma is the most frequent extracranial tumor in neonatal patients. Engineering SKNBE2 Myc-N amplified Neuroblastoma cell lines we generated individual clones expressing NDM29 non-coding-RNA at different levels. Using these cell models we documented a specific role of NDM29 in tumor cell differentiation leading to the identification of novel genes to be pharmacologically targeted for an efficient control of tumor malignancy (CA9 and MCM2 genes). Further studies taking advantage of the same models suggested the possible co-existence of different cell sub-populations in the apparently homogeneous cell culture with possible different roles in tumor maintenance and growth. Here we test this hypothesis by performing single-cell sequencing analysis and identified different sub-populations on the base of their gene expression patterns. The characterization of their specific profiles of membrane markers allowed an efficient separation of the individual populations by FACS analysis. Our preliminary results show the co-existance of cells with a marked neural phenotype with other two populations one VEGF secreting and the other VEGF recipient/responder. These preliminary findings suggest further detailed investigations of possible paracrine loops that might be at the base of tumor cell nodule growth and maintenance. Citation Format: Michele Tomanelli, Davide Ceresa, Adriana Bajetto, Paola Modesto, Paolo Malatesta, Tullio Florio, Aldo Pagano. Identification of cell sub-populations in Neuroblastoma cell lines with single-cell-sequencing analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 147.

Absorption and Transport of Phosphorus in Nodulated Soybean Plants and Diagnosis of Phosphorus Status Using Xylem Sap Analysis

Phosphorus (P) is an essential major element for plants. The absorption and transport of P are important for soybean growth and yield, including nodule growth and N2 fixation. Through an analysis of xylem sap, we investigated how nodulated soybean plants absorb PO4 via the roots and transport it to the shoot. The nodulated soybean plants were treated with 0, 50, and 250 μM PO4 concentrations for 1, 3, 7, and 15 days. The PO4 concentration in the xylem sap significantly decreased after 1 day of P deprivation, and then it gradually decreased for 15 days. The high-concentration (250 μM PO4) treatment increased the PO4 concentrations in the xylem sap at 7- and 15-day timepoints but not at the 1- or 3-day timepoints. The soybean plants were treated with 0, 25, 50, 100, 150, 250, and 500 μM PO4 for 3 days. The PO4 absorption rate increased consistently in conjunction with the increase in the PO4 concentration; however, the PO4 concentrations in the xylem sap increased only from 0 to 50 μM PO4 but were constant under higher P concentrations. The soybean plants accumulated extra PO4 in the roots. The PO4 concentration in the xylem sap immediately reflected the P deficiency conditions; thus, this index may be used as an indicator for the diagnosis of P deficiency.

Nonoperative, Active Surveillance of Larger Malignant and Suspicious Thyroid Nodules.

Active surveillance for papillary thyroid cancer (PTC) meeting criteria for surgical resection is uncommon. Which patients may prove reasonable candidates for this approach is not well defined. This work aimed to examine the feasibility and safety of active surveillance for patients with known or suspected intrathyroidal PTC up to 4 cm in diameter. A retrospective review was conducted of all consecutive patients who underwent nonoperative active surveillance of suspicious or malignant thyroid nodules over a 20-year period from 2001 to 2021. We included patients with an initial ultrasound-fine-needle aspiration confirming either (a) Bethesda 5 or 6 cytology or (b) a "suspicious" Afirma molecular test. The primary outcomes and measures included the rate of adverse oncologic outcomes (mortality and recurrence), as well as the cumulative incidence of size/volume growth. Sixty-nine patients were followed with active surveillance for 1 year or longer (average 55 months), with 26 patients (38%) having nodules 2 cm or larger. No patients were found to develop new-incident occurrence of lymph node or distant metastasis. One patient, however, demonstrated concern for progression to a dedifferentiated cancer on repeat core biopsy 17 years after initial start of nonoperative selection. A total of 21% of patients had an increase in maximum diameter more than 3 mm, while volume increase of 50% or greater was noted in 25% of patients. Thirteen patients ultimately underwent delayed (rescue) surgery, and no disease recurrence was noted after such treatment. Age and initial nodule size were not predictors of nodule growth. These data expand consideration of active surveillance of PTC in select patients with intrathyroidal suspected malignancy greater than 1 cm in diameter. Rescue surgery, if required at a later time point, appears effective.

Unregulated GmAGL82 due to Phosphorus Deficiency Positively Regulates Root Nodule Growth in Soybean.

Nitrogen fixation, occurring through the symbiotic relationship between legumes and rhizobia in root nodules, is crucial in sustainable agriculture. Nodulation and soybean production are influenced by low levels of phosphorus stress. In this study, we discovered a MADS transcription factor, GmAGL82, which is preferentially expressed in nodules and displays significantly increased expression under conditions of phosphate (Pi) deficiency. The overexpression of GmAGL82 in composite transgenic plants resulted in an increased number of nodules, higher fresh weight, and enhanced soluble Pi concentration, which subsequently increased the nitrogen content, phosphorus content, and overall growth of soybean plants. Additionally, transcriptome analysis revealed that the overexpression of GmAGL82 significantly upregulated the expression of genes associated with nodule growth, such as GmENOD100, GmHSP17.1, GmHSP17.9, GmSPX5, and GmPIN9d. Based on these findings, we concluded that GmAGL82 likely participates in the phosphorus signaling pathway and positively regulates nodulation in soybeans. The findings of this research may lay the theoretical groundwork for further studies and candidate gene resources for the genetic improvement of nutrient-efficient soybean varieties in acidic soils.

ACR Lung-RADS v2022: Assessment Categories and Management Recommendations

The American College of Radiology created the Lung CT Screening Reporting and Data System (Lung-RADS) in 2014 to standardize the reporting and management of screen-detected pulmonary nodules. Lung-RADS was updated to version 1.1 in 2019 and revised size thresholds for nonsolid nodules, added classification criteria for perifissural nodules, and allowed for short-interval follow-up of rapidly enlarging nodules that may be infectious in etiology. Lung-RADS v2022, released in November 2022, provides several updates including guidance on the classification and management of atypical pulmonary cysts, juxtapleural nodules, airway-centered nodules, and potentially infectious findings. This new release also provides clarification for determining nodule growth and introduces stepped management for nodules that are stable or decreasing in size. This article summarizes the current evidence and expert consensus supporting Lung-RADS v2022.

Lung nodule growth measurement and prediction using Multi scale - 3 D- UNet segmentation and shape variance analysis

In this work, a statistical model is constructed to forecast the possibility of lung nodules that may grow in the future. This study segments all potential lung nodule candidates using the Multi-scale 3D UNet (M-3D-UNet) method. 34 patients' CT scan series yielded an average of approximately 600 nodule candidates larger than 3 mm, which were then segmented. After removing the arteries, non-nodules and 3D shape variation analysis, 34 actual nodules remained. On actual nodules, the nodule growth Rate (NGR) was calculated in terms of 3D-volume change. Three of the 34 actual nodules had RNG values greater than one, indicating that they were malignant. Compactness, Tissue deficit, Tissue excess, Isotropic Factor and Edge gradient were used to develop the nodule growth predictive measure.

Growth and Clinical Impact of Subsolid Lung Nodules ≥6 mm During Long-Term Follow-Up After Five Years of Stability.

To investigate the incidence and timing of late growth of subsolid nodules (SSNs) ≥6 mm after initial 5-year stability, its clinical implications, and the appropriate follow-up strategy. This retrospective study included SSNs ≥6 mm that remained stable for the initial five years after detection. The incidence and timing of subsequent growth after five years of stability were analyzed using the Kaplan-Meier method. Descriptive analyses were conducted to evaluate the clinical stage shift in the SSNs, showing growth and the presence of metastasis during the follow-up period. Finally, an effective follow-up CT scan strategy for managing SSNs after a 5-year period of stability was investigated. Two hundred thirty-five eligible SSNs (211 pure ground-glass and 24 part-solid nodules) in 235 patients (median age, 63 years; 132 female) were followed for additional <1 to 181 months (median, 87.0 months; interquartile range [IQR], 47.0-119.0 months) after 5-year stability. Fourteen SSNs (6.0%) showed growth at two to 145 months (median, 96 months; IQR: 43.0-122.25 months) from the CT scan confirming 5-year stability, with the estimated cumulative incidence of growth of 0.4%, 2.1%, and 6.5% at 1, 5, and 10 years, respectively. Nine SSNs (3.8%) exhibited clinical stage shifts. No lung cancer metastases were observed. Hypothetical follow-up CT scans performed at 5, 10, and 15 years after 5-years of stability, would have detected 5 (36%), 11 (79%), and 14 (100%) of the 14 growing SSNs, along with 4 (44%), 8 (89%), and 9 (100%) of the nine stage shifts, respectively. During a long-term follow-up of pulmonary SSNs ≥6 mm after 5-years of stability, a low incidence of growth without occurrence of metastasis was noted. CT scans every five years after the initial 5-year stability period may be reasonable.

Radiological Study of Synovial Chondromatosis of the Temporomandibular Joint

Abstract Temporomandibular joint disorders (TMDs) are usually accompanied by changes in the bone structure of the TMJ brought on by degenerative processes. Osteophytes, erosion, flattening, subchondral sclerosis, pseudocysts, TMJ remodeling, articular cartilage abrasion, bone degradation, and synovial inflammation are among the characteristics of degenerative joint disease. Synovial chondromatosis (SC) is one of the degenerative joint conditions, which is defined by the growth of cartilaginous nodules, which are typically loose in the joint space of the synovial membrane. Its appearance in the TMJ, however, is more uncommon than in other large joints such as the knee and hip and is accompanied by preauricular pain, swelling, and restricted mouth opening. However, we recently encountered cases of degenerative joint disorder, i.e., of SC of TMJ, which showed the typical histopathological findings along with the typical imaging findings on Panoramic radiography (PAN) TMJ and cone-beam computed tomography images.

Deep learning-assisted development and validation of an algorithm for predicting the growth of persistent pure ground-glass nodules.

The prediction of the persistent pure ground-glass nodule (pGGN) growth is challenging and limited by subjective assessment and variation across radiologists. A chest computed tomography (CT) image-based deep learning classification model (DLCM) may provide a more accurate growth prediction. This retrospective study enrolled consecutive patients with pGGNs from January 2010 to December 2020 from two independent medical institutions. Four DLCM algorithms were built to predict the growth of pGGNs, which were extracted from the nodule areas of chest CT images annotated by two radiologists. All nodules were assigned to either the study, the inner validation, or the external validation cohort. Accuracy, sensitivity, specificity, receiver operating characteristic (ROC) curves, and areas under the ROC curve (AUROCs) were analyzed to evaluate our models. A total of 286 patients were included, with 419 pGGN. In total, 197 (68.9%) of the patients were female and the average age was 59.5±12.0 years. The number of pGGN assigned to the study, the inner validation, and the external validation cohort were 193, 130, and 96, respectively. The follow-up time of stable pGGNs for the primary and external validation cohorts were 3.66 (range, 2.01-10.08) and 4.63 (range, 2.00-9.91) years, respectively. Growth of the pGGN occurred in 166 nodules [83 (43%), 39 (30%), and 44 (45%) in the study, inner and external validation cohorts respectively]. The best-performing DLCM algorithm was DenseNet_DR, which achieved AUROCs of 0.79 [95% confidence interval (CI): 0.70, 0.86] in predicting pGGN growth in the inner validation cohort and 0.70 (95% CI: 0.60, 0.79) in the external validation cohort. DLCM algorithms that use chest CT images can help predict the growth of pGGNs.

Parameterized Gompertz-Guided Morphological AutoEncoder for Predicting Pulmonary Nodule Growth.

The growth rate of pulmonary nodules is a critical clue to the cancerous diagnosis. It is essential to monitor their dynamic progressions during pulmonary nodule management. To facilitate the prosperity of research on nodule growth prediction, we organized and published a temporal dataset called NLSTt with consecutive computed tomography (CT) scans. Based on the self-built dataset, we develop a visual learner to predict the growth for the following CT scan qualitatively and further propose a model to predict the growth rate of pulmonary nodules quantitatively, so that better diagnosis can be achieved with the help of our predicted results. To this end, in this work, we propose a parameterized Gempertz-guided morphological autoencoder (GM-AE) to generate any future-time-span high-quality visual appearances of pulmonary nodules from the baseline CT scan. Specifically, we parameterize a popular mathematical model for tumor growth kinetics, Gompertz, to predict future masses and volumes of pulmonary nodules. Then, we exploit the expected growth rate on the mass and volume to guide decoders generating future shape and texture of pulmonary nodules. We introduce two branches in an autoencoder to encourage shape-aware and textural-aware representation learning and integrate the generated shape into the textural-aware branch to simulate the future morphology of pulmonary nodules. We conduct extensive experiments on the self-built NLSTt dataset to demonstrate the superiority of our GM-AE to its competitive counterparts. Experiment results also reveal the learnable Gompertz function enjoys promising descriptive power in accounting for inter-subject variability of the growth rate for pulmonary nodules. Besides, we evaluate our GM-AE model on an in-house dataset to validate its generalizability and practicality. We make its code publicly available along with the published NLSTt dataset.

MiR-1246b, a novel miRNA molecule of extracellular vesicles in bronchoalveolar lavage fluid, promotes nodule growth through FGF14 in patients with lung cancer

With the widespread development of chest computed tomography (CT), the detection rate of pulmonary nodules has increased; therefore, the classification of benign vs. malignant nodules has become a common problem in the clinic. MicroRNA, a potential tool, is expected to become a good choice for diagnosing and studying the occurrence and development of diseases through the vector of bronchoalveolar lavage fluid extracellular vesicles (BALF-EVs). In this study, radial endobronchial ultrasound (R-EBUS) was used to locate pulmonary nodules in patients. BALF was obtained, EVs were isolated, and small RNA sequencing was performed to screen differentially expressed miRNAs between benign and malignant pulmonary nodules. The binding targets and underlying mechanisms of the differentially expressed miRNAs were verified by in vitro and in vivo experiments. R-EBUS localization and sampling was used to obtain BALF, and EVs were successfully isolated and characterized. Differentially expressed miRNAs in BALF-EVs of patients with benign vs. malignant pulmonary nodules were screened by high-throughput small RNA sequencing. A new miRNA, miR-1246b, was identified. We found that FGF14 was the binding target of miR-1246b by luciferase assay. Subsequent mechanistic studies showed that miR-1246b inhibited the expression of FGF14 in lung cancer cells, further leading to ERK phosphorylation and epithelial-to-mesenchymal transition (EMT), which ultimately contributed to lung cancer cell proliferation, migration and invasion. In summary, our study demonstrates that the detection of miRNAs in BALF-EVs, a means of liquid biopsy, could assist in distinguishing malignant nodules from benign nodules. miR-1246b, which was extracted from BALF-EVs, targets FGF14 to promote lung cancer cell proliferation, migration and invasion.

Risk and Time to Diagnosis of Lung Cancer in Incidental Pulmonary Nodules.

To determine the risk of lung cancer in incidental pulmonary nodules, as well as the time until cancer growth is detected. This retrospective study examined patients with incidental nodules detected on chest computed tomography (CT) in 2017. Characteristics of the dominant nodule were automatically extracted from CT reports, and cancer diagnoses were manually verified by a thoracic radiologist. Nodules were categorized per Fleischner Society guideline categories: solid <6mm, solid 6 to 8mm, solid >8mm, subsolid <6mm, ground glass nodules ≥6mm, and part-solid nodules ≥6mm. The time to nodule growth was determined by CT reports. A total of 3180 patients (nodules) were included, of which 155 (5%) were diagnosed with lung cancer. By category, 7/1601 (0.4%) solid nodules <6mm, 11/713 (1.5%) solid nodules 6 to 8mm, 71/446 (15.9%) solid nodules >8mm, 1/124 (0.8%) subsolid nodules <6mm, 29/202 (14.4%) ground glass nodules ≥6mm, and 36/94 (37.9%) part-solid nodules ≥6mm were malignant. Of solid lung cancers <6mm, growth was observed in 1/4 imaged by 1 year and 2/5 by 2 years; of solid lung cancers 6 to 8mm, growth was observed in 3/10 imaged by 1 year and 6/10 by 2 years. Solid nodules <6mm have a very low risk of malignancy and may not require routine follow-up. However, when malignant, growth is often not observed until 2 or more years later; therefore, stability at 1 to 2 years does not imply benignity.

Enhancing Soybean Yield: The Synergy of Sulfur and Rhizobia Inoculation.

Sulfur deficiency severely limits soybean growth, inhibiting the rhizobia nitrogenase and soybean protein synthesis. This study assessed the impact of sulfur fertilization and rhizobia inoculation on soybean growth and nitrogen fixation through bacterial culture and hydroponic experiments. We selected three rhizobia strains for bacterial cultures and used six sulfur levels. The test demonstrated severe inhibition of Rhizobium USDA110 growth without sulfur. In hydroponic experiment, we employed five sulfur levels with USDA110 as the inoculum strain. Soybean growth, nitrogen fixation, yield, and root morphology-related parameters, and root nodule growth, were significantly inhibited without sulfur. Following Rhizobium inoculation, low sulfur concentrations (0.15-0.60 mM) stimulated early-stage (V9) root growth and increased shoot nitrogen accumulation, but inhibited root growth at R5 stage. Furthermore, Rhizobium inoculation notably enhanced soybean growth, nitrogen fixation, and yield, especially within the recommended low sulfur concentration range (0.15-0.30 mM). The maximum nodule nitrogenase activity at R5 stage and highest yield was recorded at a 0.3 mM sulfur concentration with Rhizobium inoculation, which was 9.51-1222.07% higher than other treatments. These findings highlight that low sulfur concentration and rhizobia inoculation enhance soybean growth, nitrogen fixation, and yield but reduce soybean root efficacy, increasing reliance on root nodules.