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Multiple primary malignancies (MPMs) are defined as the coexistence of at least two unrelated primary malignancies in a single patient, with the tumors differing in their histology. MPMs in the same patient, when present within 6 months of the primary tumor diagnosis, are considered a synchronous occurrence. In this case report, we describe a 61-year-old man who presented with three distinct tumors concurrently in 2021: noninvasive urothelial carcinoma of the bladder, diffuse large B-cell lymphoma, and squamous cell carcinoma of the lung. We discuss the process of therapy and briefly review the literature. MPMs are increasing in incidence, requiring an interdisciplinary approach to diagnosis and treatment.

SUMMARY BILE ACID: SODIUM SYMPORTER FAMILY PROTEIN 2 (BASS2) is localized within chloroplast membranes, facilitating the translocation of pyruvate and Na+ from the cytosol to the plastid, where pyruvate supports isopentenyl diphosphate (IPP) synthesis via the methylerythritol phosphate pathway in C3 plants. Nevertheless, the biological function of BASS2 in C4 plants has not been well defined. This study unveils a previously unidentified role of PvBASS2 in Na+ and pyruvate transport in seashore paspalum (Paspalum vaginatum), a halophytic C4 grass, indicating a specific cellular function within this plant species. Data showed that overexpression of PvBASS2 in seashore paspalum attenuated salt tolerance, whereas its RNAi lines exhibited enhanced salt resistance compared to wild‐type plants, suggesting a negative regulatory role of PvBASS2 in seashore paspalum salt tolerance. The constitutive overexpression of PvBASS2 was also found to reduce salt tolerance in Arabidopsis. Further study revealed that PvBASS2 negatively regulates seashore paspalum salt tolerance, possibly due to elevated Na+/K+ ratio, disrupted chloroplast structure, and reduced photosynthetic efficiency following exposure to salinity. Importantly, our subsequent investigations revealed that modulation of PvBASS2 expression in seashore paspalum influenced carbon dioxide assimilation, intermediary metabolites of the tricarboxylic acid cycle, and enzymatic activities under salinity treatment, which in turn led to alterations in free amino acid concentrations. Thus, this study reveals a role for BASS2 in the C4 plant seashore paspalum and enhances our comprehension of salt stress responses in C4 plants. [ABSTRACT FROM AUTHOR]

Loss of AT‐interacting domain‐rich protein 1A (ARID1A) frequently occurs in human malignancies including lung cancer. The biological consequence of ARID1A mutation in lung cancer is not fully understood. This study was designed to determine the effect of ARID1A‐depleted lung cancer cells on fibroblast activation. Conditioned media was collected from ARID1A‐depleted lung cancer cells and employed to treat lung fibroblasts. The proliferation and migration of lung fibroblasts were investigated. The secretory genes were profiled in lung cancer cells upon ARID1A knockdown. Antibody‐based neutralization was utilized to confirm their role in mediating the cross‐talk between lung cancer cells and fibroblasts. NOD‐SCID‐IL2RgammaC‐null (NSG) mice received tumor tissues from patients with ARID1A‐mutated lung cancer to establish patient‐derived xenograft (PDX) models. Notably, ARID1A‐depleted lung cancer cells promoted the proliferation and migration of lung fibroblasts. Mechanistically, ARID1A depletion augmented the expression and secretion of prolyl 4‐hydroxylase beta (P4HB) in lung cancer cells, which induced the activation of lung fibroblasts through the β‐catenin signaling pathway. P4HB‐activated lung fibroblasts promoted the proliferation, invasion, and chemoresistance in lung cancer cells. Neutralizing P4HB hampered the tumor growth and increased cisplatin cytotoxic efficacy in two PDX models. Serum P4HB levels were higher in ARID1A‐mutated lung cancer patients than in healthy controls. Moreover, increased serum levels of P4HB were significantly associated with lung cancer metastasis. Together, our work indicates a pivotal role for P4HB in orchestrating the cross‐talk between ARID1A‐mutated cancer cells and cancer‐associated fibroblasts during lung cancer progression. P4HB may represent a promising target for improving lung cancer treatment. [ABSTRACT FROM AUTHOR]

Zinc finger proteins (ZFPs) are transcription factors involved in multiple cellular functions. We identified a C2H2 type ZFP (MtZPT2-2) in Medicago truncatula and demonstrated that it localizes to the nucleus and inhibits the transcription of 2 genes encoding high-affinity potassium transporters (MtHKT1;1 and MtHKT1;2). MtZPT2-2 transcripts were detected in stem, leaf, flower, seeds and roots, with the highest level in the xylem and phloem of roots and stems. MtZPT2-2 transcription in leaves was reduced after salt stress. Compared with the wild-type (WT), transgenic lines overexpressing MtZPT2-2 had decreased salt tolerance, while MtZPT2-2–knockout mutants showed increased salt tolerance. MtHKT1;1 and MtHKT1;2 transcripts and Na+ accumulation in shoots and roots, as well as in the xylem of all genotypes of plants, were increased after salt treatment, with higher levels of MtHKT1;1 and MtHKT1;2 transcripts and Na+ accumulation in MtZPT2-2–knockout mutants and lower levels in MtZPT2-2–overexpressing lines compared with the WT. K+ levels showed no significant difference among plant genotypes under salt stress. Moreover, MtZPT2-2 was demonstrated to bind with the promoter of MtHKT1;1 and MtHKT1;2 to inhibit their expression. Antioxidant enzyme activities and the gene transcript levels were accordingly upregulated in response to salt, with higher levels in MtZPT2-2–knockout mutants and lower levels in MtZPT2-2–overexpressing lines compared with WT. The results suggest that MtZPT2-2 regulates salt tolerance negatively through downregulating MtHKT1;1 and MtHKT1;2 expression directly to reduce Na+ unloading from the xylem and regulates antioxidant defense indirectly. A zinc finger transcription factor negatively regulates salt tolerance by repressing the expression of genes encoding high-affinity potassium transporters. [ABSTRACT FROM AUTHOR]

Nonnegative matrix factorization (NMF) and its numerous variants have been extensively studied and used in hyperspectral unmixing (HU). With the aid of the designed deep structure, deep NMF-based methods demonstrate advantages in exploring the hierarchical features of complex data. However, a noise corruption problem commonly exists in hyperspectral data and severely degrades the unmixing performance of deep NMF-based methods when applied to HU. In this study, we propose an ℓ 2 , 1 norm-based robust deep nonnegative matrix factorization ( ℓ 2 , 1 -RDNMF) for HU, which incorporates an ℓ 2 , 1 norm into the two stages of the deep structure to achieve robustness. The multiplicative updating rules of ℓ 2 , 1 -RDNMF are efficiently learned and provided. The efficiency of the presented method is verified in experiments using both synthetic and genuine data. [ABSTRACT FROM AUTHOR]

The noise corruption problem commonly exists in hyperspectral images (HSIs) and severely affects the accuracy of hyperspectral unmixing algorithms. The noise formulation existing in HSIs is relatively complex and would change in conjunction with different devices and imaging settings. For real applications, applying denoising approaches without accurate close-to-reality noise modeling before unmixing may not improve, but rather degrade the unmixing performance. This study proposes a robust hyperspectral unmixing method with practical learning-based hyperspectral image denoising. We formulated a close-to-reality noise model for hyperspectral data and provide a calibration approach for the noise parameters. On the basis of the calibrated noise model, synthetic data were generated and used for training a KST-based denoising network. The noisy hyperspectral data were firstly denoised by the trained denoising network and were then used to perform the unmixing process. A variety of unmixing algorithms can be integrated into our method to improve the accuracy of unmixing in noisy situations. In the experiments, several widely used unmixing algorithms were employed to verify the effect of the proposed method. The experimental results on both synthetic and real demonstrated that our proposed method can handle HSI data with various gain settings and helps to improve the unmixing performance effectively. [ABSTRACT FROM AUTHOR]

Background: Lymph node metastasis is a poor prognostic factor for lung cancer. However, the risk of lymph node metastasis has not yet been clarified. This study was conducted to analyze the predictive factors for lymph node metastasis in patients with clinical-stage IA3 lung adenocarcinoma. Methods: We retrospectively analyzed all surgical patients with clinical stage IA3 lung adenocarcinoma admitted to our hospital from January 2017 to January 2022. Three hundred and thirty-four patients underwent lobectomy combined with systematic lymph node dissection. Univariate and multivariate logistic regression analyses were used to predict the risk factors of lymph node metastasis. Results: Of the 334 patients eligible for this study, the overall lymph node metastasis rate was 15.3%. There were 45 cases with N1 metastasis, 11 cases with N2 metastasis, and five cases with both N1 and N2 metastasis. The lymph node metastasis rate was 18.1% in patients with a consolidation tumor ratio (CTR) of >0.75, 57.9% in those with >5 ng/mL carcinoembryonic antigen (CEA), and 18.0% in those with a maximum standardized uptake value of >5. Receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) for CTR and CEA was 0.790 [95% confidence interval (CI): 0.727–0.853, P < 0.001] and 0.682 (95% CI: 0.591–0.773, P < 0.001), respectively. According to multivariate regression analysis, CEA (>5 ng/mL) [odds ratio (OR) = 3.05, P = 0.016] and CTR (>0.75) (OR = 2.75, P = 0.025) were significantly correlated with lymph node metastasis of clinical stage IA3 lung adenocarcinoma. Conclusions: CEA (>5 ng/mL) and CTR (>0.75) are two important predictors of lymph node metastasis in patients with clinical stage IA3 lung adenocarcinoma. [ABSTRACT FROM AUTHOR]

Background: Mobile stroke unit (MSU) is deployed to shorten the duration of ischemic stroke recognition to thrombolysis treatment, thus reducing disability, mortality after an acute stroke attack, and related economic burden. Therefore, we conducted a comprehensive systematic review of the clinical trial and economic literature focusing on various outcomes of MSU compared with conventional emergency medical services (EMS). Methods: An electronic search was conducted in four databases (PubMed, OVID Medline, Embase, and the Cochrane Controlled Register of Trials) from 1990 to 2021. In these trials, patients with acute stroke were assigned to receive either MSU or EMS, with clinical and economic outcomes. First, we extracted interested data in the pooled population and conducted a subgroup analysis to examine related heterogeneity. We then implemented a descriptive analysis of economic outcomes. All analyses were performed with R 4.0.1 software. Results: A total of 22,766 patients from 16 publications were included. In total 7,682 (n = 33.8%) were treated in the MSU and 15,084 (n = 66.2%) in the conventional EMS. Economic analysis were available in four studies, of which two were based on trial data and the others on model simulations. The pooled analysis of time metrics indicated a mean reduction of 32.64 min (95% confidence interval: 23.38–41.89, p < 0.01) and 28.26 minutes (95% CI: 16.11–40.41, p < 0.01) in the time-to-therapy and time-to-CT completion, respectively in the MSU. However, there was no significant difference on stroke-related neurological events (OR = 0.94, 95% CI: 0.70–1.27, p = 0.69) and in-hospital mortality (OR = 1.11, 95% CI: 0.83–1.50, p = 0.48) between the MSU and EMS. The proportion of patients with modified Ranking scale (mRS) of 0–2 at 90 days from onset was higher in the MSU than EMS (p < 0.05). MSU displayed favorable benefit-cost ratios (2.16–6.85) and incremental cost-effectiveness ratio ($31,911 /QALY and $38,731 per DALY) comparing to EMS in multiple economic publications. Total cost data based on 2014 USD showed that the MSU has the highest cost in Australia ($1,410,708) and the lowest cost in the USA ($783,463). Conclusion: A comprehensive analysis of current research suggests that MUS, compared with conventional EMS, has a better performance in terms of time metrics, safety, long-term medical benefits, and cost-effectiveness. [ABSTRACT FROM AUTHOR]

Summary: Leucine‐rich repeat‐receptor‐like kinase (LRR‐RLK) is a large subfamily of plant RLKs; however, its role in cold tolerance is still unknown. A novel cold tolerance LRR‐RLK gene (MtCTLK1) in Medicago truncatula was identified using the transgenic lines overexpressing MtCTLK1 (MtCTLK1‐OE) and mtctlk1 lines with Tnt1 retrotransposon insertion. Compared with the wild‐type, MtCTLK1‐OE lines had increased cold tolerance and mtctlk1 showed decreased cold tolerance. The impaired cold tolerance in mtctlk1 could be complemented by the transgenic expression of MtCTLK1 or its homolog MfCTLK1 from Medicago falcata. Antioxidant enzyme activities and proline accumulation as well as transcript levels of the associated genes were increased in response to cold, with higher levels in MtCTLK1‐OE or lower levels in mtctlk1 lines as compared with wild type. C‐Repeat‐Binding Factors (CBFs) and CBF‐dependent cold‐responsive genes were also induced in response to cold, and higher transcript levels of CBFs and CBF‐dependent cold‐responsive genes were observed in MtCTLK1‐OE lines whereas lower levels in mtctlk1 mutants. The results validate the role of MtCTLK1 or MfCTLK1 in the regulation of cold tolerance through the CBF pathway, antioxidant defense system and proline accumulation. It also provides a valuable gene for the molecular breeding program to improve cold tolerance in crops. Significance Statement: A novel cold tolerance leucine‐rich repeat‐receptor‐like kinase was identified from Medicago truncatula. It confers cold tolerance through regulation on the C‐repeat‐binding factor cold response pathway, antioxidant defense, and proline accumulation. [ABSTRACT FROM AUTHOR]

The objective was to explore the function of gene differential expressions between lung cancer tissues and the interaction between the relevant encoded proteins, thereby analyzing the important genes closely related to lung cancer. A total of 120 samples from the GEO database (including two groups, i.e., 60 lung cancer in situ specimens and 60 normal specimens) were taken as the research objects, which were submitted to the analysis of signaling pathway, biological function enrichment, and protein interactions to reveal the molecular driving mechanism of lung cancer. Results: A total of 875 differentially expressed genes were obtained, including 291 up-regulated genes and 584 down-regulated genes. The up-regulated genes were mainly involved in biological processes such as protein metabolism, protein hydrolysis, mitosis, and cell division. Down-regulated genes were mainly involved in neutrophil chemotaxis, inflammatory response, immune response, and angiogenesis. The protein expression of high expression genes and low expression genes in patients were higher than those in the control group. The protein corresponding to the high expression gene was highly expressed in the patient group. Meanwhile, the proteins corresponding to the low expression genes were also expressed in the patient group, which showed that although the proteins corresponding to the low expression genes were low in the patients, they were still the target genes related to lung cancer. In conclusion, the molecular driving mechanism in lung cancer was mainly related to protein metabolism, proteolysis, mitosis, and cell division. It was found that TOP2A, CCNB1, CCNA2, CDK1, and TTK might be the critical target genes of lung cancer. [ABSTRACT FROM AUTHOR]

Auxin induced in root culture (AIR12) is a single gene in Arabidopsis and codes for a mono‐heme cytochrome b, but it is unknown whether plant AIR12 is involved in abiotic stress responses. MfAIR12 was identified from Medicago falcata that is legume germplasm with great cold tolerance. Transcript levels of MfAIR12 and its homolog MtAIR12 from Medicago truncatula was induced under low temperature. Overexpression of MfAIR12 led to the accumulation of H2O2 in apoplast and enhanced cold tolerance, which was blocked by H2O2 scavengers, indicating that the increased cold tolerance was dependent upon the accumulated H2O2. In addition, declined cold tolerance was observed in Arabidopsis mutant air12, which could be restored by expressing MfAIR12. Compared to the wild type, higher levels of ascorbic acid and ascorbate redox state, as well as transcripts of the C repeat/dehydration responsive element‐binding factor (CBF) transcription factors and their downstream cold‐responsive genes, were observed in MfAIR12 transgenic lines, but lower levels of those in air12 mutant. It is suggested AIR12 confers cold tolerance as a result of the altered H2O2 in the apoplast that is signaling in the regulation of CBF cold response pathway and ascorbate homeostasis. AIR12 confers cold tolerance as a result of the altered H2O2 in apoplast that is signaling in the regulation of CBF pathway and its downstream cold‐responsive genes as well as ascorbic acid synthesis and redox state. [ABSTRACT FROM AUTHOR]

Common vetch (Vicia sativa L.) is a leguminous plant used as forage and cover crops. A protocol of ethyl methanesulfonate (EMS)‐induced mutations was established in the present study, based on analysis of seed germination and emergence rate, seedling growth and abnormal plant percentage as affected by combinations of EMS concentration and treatment time. Treatment of seeds with 0.1% EMS for 9 and 12 hr or 0.5% EMS for 6 and 9 hr led to 43%–66% normal plants, which was suggested to be used for EMS‐induced mutations in common vetch. The wild‐type common vetch showed red with accumulation of anthocyanins in winter, and two lines showing separation of anthocyanin accumulation (labeled as A+) and without anthocyanin accumulation (labeled as A–) plants were selected from M2 plants induced by EMS in the field. The A– plants showing green color had higher plant height and fresh shoot weight than the A+ plants during wintering, with lower ion leakage after freezing treatment, indicating that the green mutants (A–) had increased cold tolerance. Compared to A+ plants, the green mutants had significantly increased ascorbate (AsA) level in response to low temperature treatment. The results suggest that the increased AsA level under low temperature was associated with the increased cold tolerance in the green mutants. [ABSTRACT FROM AUTHOR]

Hyperspectral unmixing (HU) is a crucial technique for exploiting remotely sensed hyperspectral data, which aims at estimating a set of spectral signatures, called endmembers and their corresponding proportions, called abundances. The performance of HU is often seriously degraded by various kinds of noise existing in hyperspectral images (HSIs). Most of existing robust HU methods are based on the assumption that noise or outlier only exists in one kind of formulation, e.g., band noise or pixel noise. However, in real-world applications, HSIs are unavoidably corrupted by noisy bands and noisy pixels simultaneously, which require robust HU in both the spatial dimension and spectral dimension. Meanwhile, the sparsity of abundances is an inherent property of HSIs and different regions in an HSI may possess various sparsity levels across locations. This article proposes a correntropy-based spatial-spectral robust sparsity-regularized unmixing model to achieve 2-D robustness and adaptive weighted sparsity constraint for abundances simultaneously. The updated rules of the proposed model are efficient to be implemented and carried out by a half-quadratic technique. The experimental results obtained by both synthetic and real hyperspectral data demonstrate the superiority of the proposed method compared to the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Hyperspectral unmixing (HU) is a crucial technique for exploiting remotely sensed hyperspectral data, which aims to estimate a set of spectral signatures, called endmembers and their corresponding proportions, called abundances. Nonnegative matrix factorization (NMF) and its various robust extensions have been widely applied to HU. Most existing robust NMF methods consider that noises only exist in one kind of formulation. However, the hyperspectral images (HSIs) are unavoidably corrupted by noisy bands and noisy pixels simultaneously in the real applications. This paper proposes a novel spectral–spatial robust NMF model by incorporating $\ell _{2,1}$ norm and $\ell _{1,2}$ norm, which achieves robustness to band noise and pixel noise simultaneously. The Huber’s M-estimator is integrated into the proposed model to achieve better assignations of weights for each pixel and band with various noise intensities, which avoids the singularity problem and effectively improves the unmixing performance. The elegant updating rules of the proposed spectral–spatial robust model are also efficiently learned and provided. Experiments are conducted on both synthetic and real hyperspectral data sets. The experimental results demonstrate the effectiveness of the proposed methods in unmixing performance. [ABSTRACT FROM AUTHOR]

Kernel nonnegative matrix factorization (KNMF) is an extension of NMF designed to capture nonlinear dependence features in data matrix through kernel functions. In KNMF, the size of the kernel matrices is closely associated with the input data matrix, of which the calculation consumes a large amount of memory and computing resource. When applied on large-scale hyperspectral data, KNMF often meets the bottleneck of memory and may cause the overflow of memory. And when dealing with dynamically acquired data, KNMF requires recomputation of the whole data set when newly acquired data arrived, which produces huge memory and computing resource requirements. To reduce the usage of memory and improve the computational efficiency when applying KNMF on large scale and dynamic hyperspectral data, we extend KNMF by introducing partition matrix theory and considering the relationships among dividing blocks. The decomposition results of hyperspectral data are derived from much smaller scale matrices containing the formerly achieved results and the newly data blocks incrementally. In this paper, we propose an incremental KNMF (IKNMF) to reduce the computing requirements for large-scale data in hyperspectral unmixing. An improved IKNMF (IIKNMF) is also proposed to further improve the abundance results of IKNMF. Experiments are conducted on both synthetic and real hyperspectral data sets. The experimental results demonstrate that the proposed methods can effectively save memory resources without degrading the unmixing performance and the proposed IIKNMF can achieve better abundance results than IKNMF and KNMF. [ABSTRACT FROM AUTHOR]

Myocardial ischemia/reperfusion (I/R) injury is a leading cause of morbidity and mortality. In this study, we investigated the role of miR-192-5p in hypoxia/reoxygenation (H/R)-induced cardiomyocyte apoptosis. H9c2 cardiomyocytes were subjected to H/R and tested for miR-192-5p expression. Overexpression and knockdown experiments were performed to determine the effects of manipulating miR-192-5p on apoptotic responses. H/R-treated H9c2 cells exhibited a 2.2-fold increase in miR-192-5p levels. Overexpression of miR-192-5p significantly augmented apoptosis in H9c2 cells after H/R, which was accompanied by a significant increase in the ratio of Bax/Bcl-2. In contrast, delivery of anti-miR-192-5p inhibitors significantly reduced apoptosis induced by H/R. FABP3 was identified to be a functional target of miR-192-5p. Restoration of FABP3 prevented apoptosis in miR-192-5p-transfected H9c2 cells, whereas downregulation of FABP3 enhanced apoptosis in H/R-exposed H9c2 cells. In conclusion, miR-192-5p mediates H/R-induced apoptosis in cardiomyocytes by targeting FABP3 and represents a potential target for prevention of myocardial I/R injury. [ABSTRACT FROM AUTHOR]

HAK/KUP/KT transporters play an important role in maintaining K+ and Na+ homeostasis in plants in response to salt stress. A salt induced PvHAK16 from halophyte seashore paspalum (Paspalum vaginatum O. Swartz) was identified in this study. PvHAK16 was localized in the plasma membrane and highly expressed in leaves but not in roots. Overexpression of PvHAK16 in Arabidopsis led to reduced seed germination rate, shoot weight, F v / F m and survival rate but increased ion leakage after salt stress as compared with the wild type. Increased Na+ and decreased K+ levels that led to higher Na+/K+ ratio was observed in transgenic lines after salt stress, which was a result of the net influx of Na+ and net efflux of K+ in transgenic plants. The results suggest that PvHAK16 confers Na+ uptake and K+ efflux under salt stress and thus negatively regulates salt tolerance. Moreover, PvHAK16 expression altered transcript levels of ion homeostasis genes K + -Uptake Permease 7 (KUP7), Potassium Transport 2/3 (AKT2), Salt Overly Sensitive 1 (SOS1) and Gated Outwardly-Rectifying K + Channel (GORK), which were associated with the increased Na+/K+ ratio in transgenic plants. Transgenic plants had reduced transcript levels of stress responsive genes and showed promoted oxidative damage as a result of reduced SOD activity and proline accumulation. • PvHAK16 negatively regulates salt tolerance with increased Na+/K+ ratio. • PvHAK16 confers Na+ uptake and K+ efflux under salt stress. • PvHAK16 expression leads to reduced proline accumulation under salt stress. [ABSTRACT FROM AUTHOR]

This paper presents a new parameterized nonlinear least squares (PNLS) algorithm for unsupervised nonlinear spectral unmixing (UNSU). The PNLS-based algorithms transform the original optimization problem with respect to the endmembers, abundances, and nonlinearity coefficients estimation into separate alternate parameterized nonlinear least squares problems. Owing to the Sigmoid parameterization, the PNLS-based algorithms are able to thoroughly relax the additional nonnegative constraint and the nonnegative constraint in the original optimization problems, which facilitates finding a solution to the optimization problems. Subsequently, we propose to solve the PNLS problems based on the Gauss–Newton method. Compared to the existing nonnegative matrix factorization (NMF)-based algorithms for UNSU, the well-designed PNLS-based algorithms have faster convergence speed and better unmixing accuracy. To verify the performance of the proposed algorithms, the PNLS-based algorithms and other state-of-the-art algorithms are applied to synthetic data generated by the Fan model and the generalized bilinear model (GBM), as well as real hyperspectral data. The results demonstrate the superiority of the PNLS-based algorithms. [ABSTRACT FROM AUTHOR]