Forest resistance to drought in a humid tropical dipterocarp forest in the Western Ghats of India

Droughts are linked to tree die-offs in the biodiverse humid tropics. We assessed drought response of a Dipterocarp Forest and found a marginal decrease in tree survival, indicating drought resistance. Understory and emergent species were sensitive to drought. Urgent focus is needed to understand drought impacts and plant physiological responses in South Asian forests.     

Chiral symmetry breaking: Experimental results and computer analysis of a liquid-phase autoxidation

The autoxidation of tetralin is treated as a model reaction system to define the applicability of stereospecific autocatalysis. This concept, predicting a spontaneous amplification of enantiomeric excess generated by an autocatalytic chemical reaction, is used in several theoretical models as an explanation for the origin of natural optical activity. The reaction system investigated obeys the basic criteria of these models: a chiral intermediate (tetralin hydroperoxide) is produced from an achiral substrate (tetralin) via an autocatalytic pathway where the feedback mechanism is expected to generate a state of broken chiral symmetry. In order to test the amplification capacity of this reaction a computer analysis of the kinetic scheme is performed. This simulation is derived from the known kinetic scheme of autoxidation and is validated by fitting the experimentally observed data of hydroperoxide evolution. Calculations show that this model allows powerful amplification of enantiomeric excess and a transient amplification of the optical rotation. It is also demonstrated that the model system exhibits pronounced sensitivity toward any loss of absolute configuration of the involved chiral species. Since an amplification effect results exclusively at a high degree of stereoselectivity, it is concluded that stereospecific autocatalysis is possible in systems which show template reactions, crystallization, or colloidal effects. © 1993 Wiley-Liss, Inc.     

A mechanistic spatio-temporal modeling of COVID-19 data

Understanding the evolution of an epidemic is essential to implement timely and efficient preventive measures. The availability of epidemiological data at a fine spatio-temporal scale is both novel and highly useful in this regard. Indeed, having geocoded data at the case level opens the door to analyze the spread of the disease on an individual basis, allowing the detection of specific outbreaks or, in general, of some interactions between cases that are not observable if aggregated data are used. Point processes are the natural tool to perform such analyses. We analyze a spatio-temporal point pattern of Coronavirus disease 2019 (COVID-19) cases detected in Valencia (Spain) during the first 11 months (February 2020 to January 2021) of the pandemic. In particular, we propose a mechanistic spatio-temporal model for the first-order intensity function of the point process. This model includes separate estimates of the overall temporal and spatial intensities of the model and a spatio-temporal interaction term. For the latter, while similar studies have considered different forms of this term solely based on the physical distances between the events, we have also incorporated mobility data to better capture the characteristics of human populations. The results suggest that there has only been a mild level of spatio-temporal interaction between cases in the study area, which to a large extent corresponds to people living in the same residential location. Extending our proposed model to larger areas could help us gain knowledge on the propagation of COVID-19 across cities with high mobility levels.     

单增李斯特菌胎盘感染的体内外模型研究进展

单核细胞增生李斯特氏菌（Listeria monocytogenes）是重要的食源性致病菌,能引发人类的李斯特菌病,是全球公共卫生问题之一。该菌易感染孕妇,引起胎儿和新生儿的侵袭性李斯特菌病,严重威胁母婴健康。因此,建立有效的单增李斯特菌感染胎盘体内外模型,解析和探究单增李斯特菌经胎盘感染机制,是预防和控制单增李斯特菌感染母婴的关键所在。本文综述了可用于研究单增李斯特菌母婴感染的体内外胎盘模型,总结和讨论了各类模型的优势和局限性;并着重分析了体外三维胎盘屏障模型在单增李斯特菌感染方面的研究进展和未来研究方向。以期为深入解析该菌经胎盘感染的途径、发病机制提供支持,并为预防和控制母婴李斯特菌病提供科学参考。     

Automatic Detection of Severely and Mildly Infected COVID-19 Patients with Supervised Machine Learning Models

ObjectivesWhen the prognosis of COVID-19 disease can be detected early, the intense-pressure and loss of workforce in health-services can be partially reduced. The primary-purpose of this article is to determine the feature-dataset consisting of the routine-blood-values (RBV) and demographic-data that affect the prognosis of COVID-19. Second, by applying the feature-dataset to the supervised machine-learning (ML) models, it is to identify severely and mildly infected COVID-19 patients at the time of admission.Material and methodsThe sample of this study consists of severely (n = 192) and mildly (n = 4010) infected-patients hospitalized with the diagnosis of COVID-19 between March-September, 2021. The RBV-data measured at the time of admission and age-gender characteristics of these patients were analyzed retrospectively. For the selection of the features, the minimum-redundancy-maximum-relevance (MRMR) method, principal-components-analysis and forward-multiple-logistics-regression analyzes were used. The features set were statistically compared between mild and severe infected-patients. Then, the performances of various supervised-ML-models were compared in identifying severely and mildly infected-patients using the feature set.ResultsIn this study, 28 RBV-parameters and age-variable were found as the feature-dataset. The effect of features on the prognosis of the disease has been clinically proven. The ML-models with the highest overall-accuracy in identifying patient-groups were found respectively, as follows: local-weighted-learning (LWL)-97.86%, K-star (K*)-96.31%, Naive-Bayes (NB)-95.36% and k-nearest-neighbor (KNN)-94.05%. Also, the most successful models with the highest area-under-the-receiver-operating-characteristic-curve (AUC) values in identifying patient groups were found respectively, as follows: LWL-0.95%, K*-0.91%, NB-0.85% and KNN-0.75%.ConclusionThe findings in this article have significant a motivation for the healthcare professionals to detect at admission severely and mildly infected COVID-19 patients.     

Propolis Enhances 5-Fluorouracil Mediated Antitumor Efficacy and Reduces Side Effects in Colorectal Cancer: An in Vitro and in Vivo Study

In this study, we investigated the combined treatment of 5-fluorouracil (5-FU) and Anatolian propolis extract (PE) on colorectal cancer (CRC)using in vitro and in vivo studies. We exposed luciferase-transfected (Lovo-Luc CRC) cells and healthy colon cells (CCD-18Co) to varying concentrations of 5-FU and PE to assess their genotoxic, apoptotic, and cytotoxic effects, as well as their intracellular reactive oxygen species (iROS) levels. We also developed a xenograft model in nude mice and evaluated the anti-tumor effects of PE and 5-FU using various methods. Our findings showed that the combination of PE and 5-FU had selectivity against cancer cells, particularly at higher doses, and enhanced the anti-tumor effectiveness of 5-FU against colon CRC. The results suggest that PE can reduce side effects and increase the effectiveness of 5-FU through iROS generation in a dose-dependent manner.     

Inferring landscape resistance to gene flow when genetic drift is spatially heterogeneous

In connectivity models, land cover types are assigned cost values characterizing their resistance to species movements. Landscape genetic methods infer these values from the relationship between genetic differentiation and cost distances. The spatial heterogeneity of population sizes, and consequently genetic drift, is rarely included in this inference although it influences genetic differentiation. Similarly, migration rates and population spatial distributions potentially influence this inference. Here, we assessed the reliability of cost value inference under several migration rates, population spatial patterns and degrees of population size heterogeneity. Additionally, we assessed whether considering intra-population variables, here using gravity models, improved the inference when drift is spatially heterogeneous. We simulated several gene flow intensities between populations with varying local sizes and spatial distributions. We then fit gravity models of genetic distances as a function of (i) the ‘true’ cost distances driving simulations or alternative cost distances, and (ii) intra-population variables (population sizes, patch areas). We determined the conditions making the identification of the ‘true’ costs possible and assessed the contribution of intra-population variables to this objective. Overall, the inference ranked cost scenarios reliably in terms of similarity with the ‘true’ scenario (cost distance Mantel correlations), but this ‘true’ scenario rarely provided the best model goodness of fit. Ranking inaccuracies and failures to identify the ‘true’ scenario were more pronounced when migration was very restricted (<4 dispersal events/generation), population sizes were most heterogeneous and some populations were spatially aggregated. In these situations, considering intra-population variables helps identify cost scenarios reliably, thereby improving cost value inference from genetic data.     

Hepatic Gluconeogenesis and the Activity of PDH in Individual Tissues of GTG-Obese Mice Following Adrenalectomy

Adrenalectomy (ADX) lowers circulating glucose levels in animal models of non-insulin dependent diabetes (NIDDM) and obesity. To investigate the role of hepatic glucose production (HGP) and tissue glucose oxidation in the improvement in glucose tolerance, hepatocyte gluconeogenesis and the activity of pyruvate dehydrogenase (PDH) were examined in different tissues of gold thioglucose (GTG) obese mice 2 weeks after ADX or sham ADX. GTG-obese mice which had undergone ADX weighed significantly less than their adrenal intact counterparts (GTG ADX: 37.5 ± 0.7g; GTG: 44.1 ± 0.4g; p<0.05), and demonstrated lower serum glucose (GTG ADX: 22.5 ± 1.6 mmol/L; GTG: 29.4 ± 1.9 mmol/L; p<0.05) and serum insulin levels (GTG ADX: 76 ± 10μ.U/mL; GTG: 470 ± 63μU/mL; p<0.05). Lactate conversion to glucose by hepatocytes isolated from ADX GTG mice was significantly reduced compared with that of hepatocytes from GTG mice (GTG ADX: 125 ± 10 nmol glucose/10⁶ cells; GTG: 403 ± 65 nmol glucose/10⁶ cells; p<0.05). ADX also significantly reduced both the glycogen (GTG ADX: 165 ± 27 μmol/liver; GTG: 614 ± 60 pmol/Iiver; p<0.05) and fatty acid content (GTG ADX: 101 ± 9 mg fatty acid/g liver; GTG: 404 ± 40 mg fatty acid/g liver; p<0.05) of the liver of GTG-obese mice. ADX of GTG-obese mice reduced PDH activity by varying degrees in all tissues, except quadriceps muscle. These observations are consistent with an ADX induced decrease in hepatic lipid stores removing fatty acid-induced increases in gluconeogenesis and increased peripheral availability of fatty acids inhibiting PDH activity via the glucose/fatty acid cycle. It is also evident that the improvement in glucose tolerance which accompanies ADX of GTG-obese mice is not due to increased PDH activity resulting in enhanced peripheral glucose oxidation. Instead, it is more likely that reduced blood glucose levels after ADX of GTG-obese mice are the result of decreased gluconeogenesis in the liver.     

三尖杉的组织培养－紫杉醇来源的新途径

从三尖杉当年生幼茎和未成熟假种皮诱导出了愈伤组织,对愈伤组织进行了培养研究,ＨＰＬＣ分析表明其紫杉醇和１０－ｄＡＢⅢ分别为细胞干重的０．００２０９％和０．０１２２％。三尖杉可望成为紫杉醇来源的新途径。