Study of blood level and fluorescence in infrared light thoracoscopic segmentectomy using Indocyanine Green - Relationship between blood levels of indocyanine green and fluorescence during segmentectomy.
Efficacy of Acupuncture and moxibustion Treatment for Opioid-Induced Constipation in Patients with Cancer Pain. An Open-Label, Randomized Controlled Trial - Acupuncture and moxibustion treatment for constipation in cancer patients (RCT)
While lodging in wheat appears to correlate with the ratio of canopy coverage at the initiation of stem elongation (CC30), a mechanistic understanding of the relationship between lodging index and CC30 is lacking. The objective of this study was to examine more closely the relationship between lodging and CC30 and to identify the most effective sowing densities and/or planting patterns in reducing lodging. The CC30 was adjusted by varying the sowing d. and planting pattern, i.e., wide vs narrow-spaced rows and altering the seed spacing within the row and by spread sowing. We found that CC30 was pos. correlated with the lodging degree at maturity and was neg. correlated with internode dry weight per unit length. The CC30 for a sowing d. of 3 g m-2 (which is about half the conventional sowing d. in Japan) was low at a range of 28-75 %. In these treatments, CC30 was lowest under spread sowing where the spacing between plants was greatest. The yield of the 3 g m-2 spread-seed treatments was more than 500 g m-2. This yield is comparable to that of the other treatments even though the sowing d. was much lower. The aboveground N accumulation at maturity of the 3 g m-2 spread-seed treatments was similar to that of the other treatments. As found in the spread-seed treatments, our results suggest that lowering CC30 by reducing the sowing d. and/or by changing the planting pattern, increased the spacing between seedlings and thus helped to prevent lodging while still retaining high yields.
2023-07-07·Physical review letters
Demonstration of a bosonic quantum classifier with data re-uploading
In a single qubit system, a universal quantum classifier can be realized using the data reuploading technique. In this study, we propose a new quantum classifier applying this technique to bosonic systems and successfully demonstrate it using a silicon-based photonic integrated circuit. We established a theory of quantum machine learning algorithm applicable to bosonic systems and implemented a programmable optical circuit combined with an interferometer. Learning and classification using part of the implemented optical quantum circuit with uncorrelated two photons resulted in a classification with a success probability of 94±0.8% in the proof of principle experiment. As this method can be applied to an arbitrary two-mode N-photon system, further development of optical quantum classifiers, such as extensions to quantum entangled and multiphoton states, is expected in the future.
RNF128 expression in lung adenocarcinoma is a favorable prognostic factor associated with decreased tumor-associated macrophages
Molecular-level research has linked RING finger (RNF) protein family members to carcinogenesis and tumor progression. Among them, RNF128 is related to tumor progression, but reports on its association with lung cancer are few. This study aimed to clarify the unknown association between RNF128 expression and clinical outcomes in patients with lung adenocarcinoma.
Clinical data of 545 patients with therapy-naïve lung adenocarcinoma who underwent lobectomy with systematic lymph node dissection between 1999 and 2016 were retrospectively reviewed. Histological and immunohistochemical analyses were conducted to evaluate the relationship between RNF128 expression and prognosis.
Among adenocarcinoma histologic types, acinar, micropapillary, and solid tumors did not express RNF128 compared with other histologic types (p < 0.001). Patients with high RNF128 expression exhibited fewer clusters of differentiated (CD) 68+ tumor-associated macrophages (TAMs) and CD163+ TAMs. Multivariate analysis of relapse-free survival (RFS) and overall survival (OS) revealed that the lack of RNF128 expression was an independent prognostic factor for poor RFS (hazard ratio [HR] 1.60, p = 0.029) and OS (HR 1.83, p = 0.041), suggesting that RNF128 expression is a favorable prognostic factor.
RNF128 expression may be an independent predictor of favorable outcomes in Japanese patients with untreated lung adenocarcinoma who undergo surgical resection. Further elucidation of the role of TAM-related E3 ubiquitin ligase in immune function may facilitate the development of effective immunomodulatory therapies for lung adenocarcinoma.
Two novel hypotheses have been proposed that address the 'two-fold cost of sex': one of the biggest enigmas in the evolution of sexual reproduction.
Two novel hypotheses have been proposed that address the "two-fold cost of sex": one of the biggest enigmas in the evolution of sexual reproduction.
The evolution of sexual reproduction in living beings is one of the biggest mysteries in biology. There are two known modes of reproduction: asexual, where the organism creates clones of itself, and sexual, where gametes from two individuals fuse to give rise to progeny. There are many hypotheses that address various aspects of the evolution of sexual reproduction; nonetheless, there are also many questions that are still unanswered.
The biggest question in the study of the evolution of sexual reproduction is the question of cost. Sexual reproduction requires exponentially more energy than asexual reproduction. Nevertheless, sexual reproduction has two major advantages over asexual reproduction: it results in genetic diversity in offspring, and it eliminates harmful mutations.
Associate Professor Eisuke Hasegawa of Hokkaido University and Associate Professor Yukio Yasui of Kagawa University have proposed and modeled two novel hypotheses which address two open questions in the study of the evolution of sexual reproduction. Their hypotheses were published in the Journal of Ethology.
The researchers proposed hypotheses to address the "two-fold cost of sex": the cost of meiosis and the cost of producing large numbers of male gametes. Sexual reproduction can be isogamous, where the gametes are all of the same size, or it can be anisogamous, where the female gametes are large, while the male gametes are small and numerous. The hypotheses were tested by computer modelling.
The first hypothesis they proposed is the "seesaw effect" by which a large number of harmful mutations are eliminated. The first individual to have a sex-controlling gene -- that allowed for meiosis to occur -- produced four gametes. Only gametes with the sex-controlling gene could fuse, fixing it in the population and erasing the cost of meiosis. In addition, any harmful mutations were diluted or discarded depending on whether they were associated with the sex-controlling gene.
The second hypothesis, the development of anisogamy via "inflated isogamy," was developed from the first hypothesis. They suggest that, originally, multicellular organisms with higher energy generation evolved; then, the gamete size increased ("inflated isogamy") as the increased resources in larger gametes increased the survival rate of offspring. Then, the male gametes reduced in size to fertilize more female gametes -- depending on the inflated female gametes to provide the resources for survival. This strategy does not involve any extra cost on the part of the female; in fact, it may have triggered their counteradaptation to the current-day meiosis in females that results in just one female gamete (the oocyte) per gametocyte.
With these hypotheses, the authors have addressed the question of "two-fold cost of sex," and have also hypothesized that the first sexual reproduction required only one individual, and was a self-fertilizing event. However, the two hypotheses are still in their initial stages, and further work is required to address specific assumptions and conclusions underlying them.
When the evolution of towns and of roads are modeled together, the natural landscape alone is enough to predict the actual arrangement of real towns.
The phrase "All roads lead to Rome" captures in five words how important roads are for important cities. Yet, when we think of what made some towns last and grow and others shrink and be forgotten, we often think first of cultural and political events, the climate, land productivity and geography. As a consequence, most current scientific models of how cities develop treat roads as by-products or exogenous factors and they need a large amount of socio-economic data to be able to reproduce the cities' arrangement.
In a paper published in Scientific Reports, Kagawa University's Takaaki Aoki, Tohoku University's Naoya Fujiwara, Hokkaido University's Toshiyuki Nakagaki and University of Oxford's Mark Fricker found that all they need to explain the distribution of towns in Italy was, first, a small set of mathematical equations that explain how the population of places and the connections between them interact; and second, a map containing the relief of the considered landscape. They emphasized: "Landscape on its own is not sufficient to explain the population distribution as a form of geographical determinism, but requires the inter-dependent dynamical feedback between population and the transport network emerging in parallel."
The computational model Aoki and his colleagues constructed is based on a grid of cells that each have a terrain and slope as well as populations. In each round of the model, the computer evaluates how the road networks between each point in the map to every other point grow or shrink depending on how popular the endpoints are; and vice versa, how the populations of each cell change as a result of how well connected it is to all other cells. The landscape enters the calculation via road networks through different kinds of terrain being more or less attractive. While these conditions alone already produce results fairly similar to the real-world distribution of towns, the researchers could further increase the accuracy by including "history" into their model, by starting their simulation with the population being distributed as in ancient Roman times and by increasing the length of typical journeys as time progressed.
However, the model the researchers developed can in no case recreate the distribution of modern towns completely accurately, with some towns being larger or smaller in the model than in reality and their locations not always matching perfectly. The researchers admit that there are many important details, such as small-scale landscape features or historical events, that would significantly increase the accuracy of their model. But they maintain that it still "provides a baseline reference tool to predict the expected population distribution when constrained solely by topography." This is all the more remarkable since in many alternative models, the relief of the natural landscape is not even explicitly considered.
The researchers argue that, using their model as a "sophisticated null model," future work could quantify the importance of socio-economic, environmental, and other factors that are responsible for the deviations from real-world data. Thus, they hope to pioneer "a new direction to deconstruct the complex phenomena of human civilization involving many natural and social factors."