Mycoremediation of lead and cadmium by lignocellulosic enzymes of Pleurotus eryngii.

This study aimed to investigate the ability of Pleurotus eryngii fungus to absorb lead and cadmium from industrial wastewater. After culturing the fungus on a potato dextrose agar (PDA) medium containing 0 (control), 150 mg L-1, 250 mg L-1, and 350 mg L-1 concentrations of lead and cademium for 30 days, the mycelia were isolated from the culture medium and their extracts were used to measure protein content and the activity of antioxidant enzymes. Also, heavy metal contents were analyzed by atomic absorption spectrometry using flame photometry. Results showed that the growth of mycelia was significantly affected by different concentrations of the two heavy metals. High tolerance of heavy metal pollution in the culture media and the ability to accumulate lead and cademium confirmed that Pleurotus eryngii is a favorable option for mycoremediation. Also, molecular studies for fungal sequencing were investigated using the trench method, the sequence of the fungus was recorded in the gene bank, and finally the fungus was identified in the study.

Melatonin Confers NaCl Tolerance in Withaniacoagulans L. by Maintaining Na+/K+ Homeostasis, Strengthening the Antioxidant Defense System and Modulating Withanolides Synthesis-Related Genes.

As a multifunctional signaling molecule, melatonin (ML) is widely considered to induce the defense mechanism and increase the accumulation of secondary metabolites under abiotic stresses. Here, the effects of different concentrations of ML (100 and 200 µM) on the biochemical and molecular responses of Withania coagulans L. in hydroponic conditions under 200 mM NaCl treatment were evaluated. The results showed that NaCl treatment impaired photosynthetic function and reduced plant growth by decreasing photosynthetic pigments and gas exchange parameters. NaCl stress also induced oxidative stress and membrane lipid damage, disrupting Na+/K+ homeostasis and increasing hydrogen peroxide levels. NaCl toxicity decreased nitrogen (N) assimilation activity in leaves by reducing the activity of enzymes associated with N metabolism. However, adding ML to NaCl-stressed plants improved gas exchange parameters and increased photosynthesis efficiency, resulting in improved plant growth. By enhancing the activity of antioxidant enzymes and reducing hydrogen peroxide levels, ML ameliorated NaCl-induced oxidative stress. By improving N metabolism and restoring Na+/K+ homeostasis in NaCl-stressed plants, ML improved N uptake and plant adaptation to salinity. ML increased the expression of genes responsible for the biosynthesis of withanolides (FPPS, SQS, HMGR, DXS, DXR, and CYP51G1) and, as a result, increased the accumulation of withanolides A and withaferin A in leaves under NaCl stress. Overall, our results indicate the potential of ML to improve plant adaptation under NaCl stress through fundamental changes in plant metabolism. Supplementary Information: The online version contains supplementary material available at 10.1134/S1021443723600125.

No Tradeoff between Coherence and Sub-Poissonianity for Heisenberg-Limited Lasers.

The Heisenberg limit to laser coherence C-the number of photons in the maximally populated mode of the laser beam-is the fourth power of the number of excitations inside the laser. We generalize the previous proof of this upper bound scaling by dropping the requirement that the beam photon statistics be Poissonian (i.e., Mandel's Q=0). We then show that the relation between C and sub-Poissonianity (Q<0) is win-win, not a tradeoff. For both regular (non-Markovian) pumping with semiunitary gain (which allows Q→-1), and random (Markovian) pumping with optimized gain, C is maximized when Q is minimized.

Thermodynamics from first principles: Correlations and nonextensivity.

The standard formulation of thermostatistics, being based on the Boltzmann-Gibbs distribution and logarithmic Shannon entropy, describes idealized uncorrelated systems with extensive energies and short-range interactions. In this Rapid Communication, we use the fundamental principles of ergodicity (via Liouville's theorem), the self-similarity of correlations, and the existence of the thermodynamic limit to derive generalized forms of the equilibrium distribution for long-range-interacting systems. Significantly, our formalism provides a justification for the well-studied nonextensive thermostatistics characterized by the Tsallis distribution, which it includes as a special case. We also give the complementary maximum entropy derivation of the same distributions by constrained maximization of the Gibbs-Shannon entropy. The consistency between the ergodic and maximum entropy approaches clarifies the use of the latter in the study of correlations and nonextensive thermodynamics.

Finding the ground states of symmetric infinite-dimensional Hamiltonians: explicit constrained optimizations of tensor networks.

Understanding extreme non-locality in many-body quantum systems can help resolve questions in thermostatistics and laser physics. The existence of symmetry selection rules for Hamiltonians with non-decaying terms on infinite-size lattices can lead to finite energies per site, which deserves attention. Here, we present a tensor network approach to construct the ground states of nontrivial symmetric infinite-dimensional spin Hamiltonians based on constrained optimizations of their infinite matrix product states description, which contains no truncation step, offers a very simple mathematical structure, and other minor advantages at the cost of slightly higher polynomial complexity in comparison to an existing method. More precisely speaking, our proposed algorithm is in part equivalent to the more generic and well-established solvers of infinite density-matrix renormalization-group and variational uniform matrix product states, which are, in principle, capable of accurately representing the ground states of such infinite-range-interacting many-body systems. However, we employ some mathematical simplifications that would allow for efficient brute-force optimizations of tensor-network matrices for the specific cases of highly-symmetric infinite-size infinite-range models. As a toy-model example, we showcase the effectiveness and explain some features of our method by finding the ground state of the U(1)-symmetric infinite-dimensional antiferromagnetic XX Heisenberg model.

Combined analysis of biomarkers of proliferation and apoptosis in colon cancer: an immunohistochemistry-based study using tissue microarray.

BACKGROUND: Disturbance of the balance between proliferation and apoptosis is an important hallmark of tumor development. The goal of this study was to develop a descriptive parameter that represents this imbalance and relate this parameter to clinical outcome in all four stages of colon cancer. MATERIAL AND METHODS: The study population consisted of 285 stage I-IV colon cancer patients of which a tumor tissue microarray (TMA) was available. TMA sections were immunohistochemically stained and quantified for the presence of Ki67 and cleaved caspase-3 tumor expression. These results were used to develop the combined apoptosis proliferation (CAP) parameter and correlated to patient outcome. RESULTS: The CAP parameter was significantly related to clinical outcome; patients with CAP ++ (high level of both apoptosis and proliferation) showed the best outcome perspectives (overall survival (OS), p = 0.004 and disease-free survival (DFS), p = 0.009). The effect of the CAP parameter was related to tumor microsatellite status and indirectly to tumor location, where left-sided tumors with CAP + - (high level of proliferation, low level of apoptosis) showed a worse prognosis (DFS p value 0.02) and right-sided tumors with CAP + - had a better prognosis (DFS p value 0.032). With stratified analyses, the CAP parameter remained significant in stage II tumors only. CONCLUSIONS: The CAP parameter, representing outcome of the balance between the level of apoptosis and proliferation, can be used as a prognostic marker in colon cancer patients for both DFS and OS, particularly in left-sided, microsatellite stable tumors when tumor-node-metastasis (TNM) stage is taken into account.

Combined analysis of HLA class I, HLA-E and HLA-G predicts prognosis in colon cancer patients.

BACKGROUND: Evasion of immune surveillance and suppression of the immune system are important hallmarks of tumour development in colon cancer. The goal of this study was to establish a tumour profile based on biomarkers that reflect a tumour's immune susceptibility status and to determine their relation to patient outcome. METHODS: The study population consisted of 285 stage I-IV colon cancer patients of which a tissue micro array (TMA) was available. Sections were immunohistochemically stained for the presence of Foxp3+ cells and tumour expression of HLA Class I (HLA-A, -B, -C) and non-classical HLA-E and HLA-G. All markers were combined for further analyses, resulting in three tumour immune phenotypes: strong immune system tumour recognition, intermediate immune system tumour recognition and poor immune system tumour recognition. RESULTS: Loss of HLA class I expression was significantly related to a better OS (P-value 0.005) and DFS (P-value 0.008). Patients with tumours who showed neither HLA class I nor HLA-E or -G expression (phenotype a) had a significant better OS and DFS (P-value <0.001 and 0.001, respectively) compared with phenotype b (OS HR: 4.7, 95% CI: 1.2-19.0, P=0.001) or c (OS HR: 8.2, 95% CI: 2.0-34.2, P=0.0001). Further, the tumour immune phenotype was an independent predictor for OS and DFS (P-value 0.009 and 0.013, respectively). CONCLUSION: Tumours showing absence of HLA class I, HLA-E and HLA-G expressions were related to a better OS and DFS. By combining the expression status of several immune-related biomarkers, three tumour immune phenotypes were created that related to patient outcome. These immune phenotypes represented significant, independent, clinical prognostic profiles in colon cancer.

Expression of cell adhesion molecules and prognosis in breast cancer.

BACKGROUND: Cell adhesion molecules (CAMs) play an important role in the process of metastasis. The prognostic value of tumour expression of N-cadherin, E-cadherin, carcinoembryonic antigen (CEA) and epithelial CAM (Ep-CAM) was evaluated in patients with breast cancer. METHODS: A tissue microarray of the patient cohort was stained immunohistochemically for all markers and analysed by microscopy. Expression was classified into two categories, with the median score as cut-off level. For CEA, the above-median category was further subdivided in two subgroups based on staining intensity (low or high intensity). RESULTS: The cohort consisted of 574 patients with breast cancer with a median follow-up of 19 years. Below-median expression of E-cadherin (P = 0·015), and above-median expression of N-cadherin (P = 0·004), Ep-CAM (P = 0·046) and CEA (P = 0·001) all resulted in a shorter relapse-free period. Multivariable analysis revealed E-cadherin and CEA to be independent prognostic variables. Combined analysis of CEA and E-cadherin expression showed a 3·6 times higher risk of relapse for patients with high-intensity expression of CEA, regardless of E-cadherin expression, compared with patients with below-median CEA and above-median E-cadherin tumour expression (hazard ratio 3·60, 95 per cent confidence interval 2·12 to 6·11; P < 0·001). An interaction was found between expression of these two CAMs (P < 0·001), suggesting a biological association. CONCLUSION: Combining E-cadherin and CEA tumour expression provides a prognostic parameter with high discriminative power that is a candidate tool for prediction of prognosis in breast cancer.