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There is little evidence in the literature about the relationship between frailty and falls in older adults. Our objective was to explore the relationship between frailty and falls, and to analyze the effect factors (e.g., gender, different frailty assessment tools, areas, level of national economic development, and year of publication) of the association between frailty and falls among older adults. Systematic review and meta-analysis. Cohort studies that evaluated the association between frailty and falls in the older adults were included. We excluded any literature outside of cohort studies. We did a systematic literature search of English databases PubMed, Scopus, Web of Science, EBSCOhost, and SciElO, as well as the Chinese databases CNKI, WANFANG, and VIP from 2001 until October 2022. The eligible studies were evaluated for potential bias using the Newcastle-Ottawa Scale (NOS). Study selection, data extraction and assessment of study quality were each conducted by two investigators. In Stata/MP 17.0 software, we calculated pooled estimates of the prevalence of falls by using a random-effects model, Subgroup analysis was conducted based on gender, different frailty assessment tools, areas, level of economic development, and year of publication. The results are presented using a forest plot. Twenty-nine studies were included in this meta-analysis and a total of 1,093,270 participants aged 65 years and above were enrolled. Among the older adults, frailty was significantly associated with a higher risk for falls, compared with those without frailty (combined RR-relative risk = 1.48, 95% CI-confidence interval: 1.27–1.73, I2=98.9%). In addition, the results of subgroup analysis indicated that men had a higher risk for falls than women among the older adults with frailty (RR 1.94, 95% CI: 1.18–3.2 versus RR 1.44, 95% CI: 1.24–1.67). Subgroup analysis by different frailty assessment tools revealed an increased risk of falls in older adults with frailty when assessed using the Frailty Phenotype (combined RR 1.32, 95%CI: 1.17–1.48), FRAIL score (combined RR 1.82, 95%CI: 1.36–2.43), and Study of Osteoporotic Fractures index (combined RR 1.54, 95%CI: 1.10–2.16). Furthermore, subgroup analysis by areas and level of national economic development found the highest fall risk in Oceania (combined RR 2.35, 95%CI: 2.28–2.43) and the lowest in Europe (combined RR 1.20, 95%CI: 1.05–1.38). Developed countries exhibited a lower fall risk compared to developing countries (combined RR 1.44, 95%CI: 1.21–1.71). Analysis by year of publication showed the highest fall risk between 2013–2019 (combined RR 1.79, 95%CI: 1.45–2.20) and the lowest between 2001–2013 (combined RR 1.21, 95%CI: 1.13–1.29). Frailty represents a significant risk factor for falls in older adults, with the degree of risk varying according to the different frailty assessment tools employed, and notably highest when using the FRAIL scale. Additionally, factors such as gender, areas, level of national economic development, and healthcare managers' understanding of frailty may all impact the correlation between frailty and falls. Thus, it's imperative to select suitable frailty diagnostic tools tailored to the specific characteristics of the population in question. This, in turn, facilitates the accurate identification of frailty in older adults and informs the development of appropriate preventive and therapeutic strategies to mitigate fall risk.

The response of the Indian summer monsoon (ISM) circulation and precipitation to Middle East dust aerosols on sub-seasonal timescales is studied using observations and the Weather Research and Forecasting model coupled with online chemistry (WRF-Chem). Satellite data show that the ISM rainfall in coastal southwest India, central and northern India, and Pakistan is closely associated with the Middle East dust aerosols. The physical mechanism behind this dust–ISM rainfall connection is examined through ensemble simulations with and without dust emissions. Each ensemble includes 16 members with various physical and chemical schemes to consider the model uncertainties in parameterizing short-wave radiation, the planetary boundary layer, and aerosol chemical mixing rules. Experiments show that dust aerosols increase rainfall by about 0.44 mm day−1 (~10 % of the climatology) in coastal southwest India, central and northern India, and north Pakistan, a pattern consistent with the observed relationship. The ensemble mean rainfall response over India shows a much stronger spatial correlation with the observed rainfall response than any other ensemble members. The largest modeling uncertainties are from the boundary layer schemes, followed by short-wave radiation schemes. In WRF-Chem, the dust aerosol optical depth (AOD) over the Middle East shows the strongest correlation with the ISM rainfall response when dust AOD leads rainfall response by about 11 days. Further analyses show that increased ISM rainfall is related to enhanced southwesterly monsoon flow and moisture transport from the Arabian Sea to the Indian subcontinent, which are associated with the development of an anomalous low-pressure system over the Arabian Sea, the southern Arabian Peninsula, and the Iranian Plateau due to dust-induced heating in the troposphere. The dust-induced heating in the mid-upper troposphere is mainly located in the Iranian Plateau rather than the Tibetan Plateau. This study demonstrates a thermodynamic mechanism that links remote desert dust emissions in the Middle East to ISM circulation and precipitation variability on sub-seasonal timescales, which may have implications for ISM rainfall forecasts.

Background Accurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients’ treatment. The current heavy workload of pathologists in clinics/hospitals may easily lead to unconscious misdiagnosis of CRC based on daily image analyses. Methods Based on a state-of-the-art transfer-learned deep convolutional neural network in artificial intelligence (AI), we proposed a novel patch aggregation strategy for clinic CRC diagnosis using weakly labeled pathological whole-slide image (WSI) patches. This approach was trained and validated using an unprecedented and enormously large number of 170,099 patches, > 14,680 WSIs, from > 9631 subjects that covered diverse and representative clinical cases from multi-independent-sources across China, the USA, and Germany. Results Our innovative AI tool consistently and nearly perfectly agreed with (average Kappa statistic 0.896) and even often better than most of the experienced expert pathologists when tested in diagnosing CRC WSIs from multicenters. The average area under the receiver operating characteristics curve (AUC) of AI was greater than that of the pathologists (0.988 vs 0.970) and achieved the best performance among the application of other AI methods to CRC diagnosis. Our AI-generated heatmap highlights the image regions of cancer tissue/cells. Conclusions This first-ever generalizable AI system can handle large amounts of WSIs consistently and robustly without potential bias due to fatigue commonly experienced by clinical pathologists. It will drastically alleviate the heavy clinical burden of daily pathology diagnosis and improve the treatment for CRC patients. This tool is generalizable to other cancer diagnosis based on image recognition.

The aim of the present study is to evaluate the potential ecological risk and trend of soil heavy-metal pollution around a coal gangue dump in Jilin Province (Northeast China). The concentrations of Cd, Pb, Cu, Cr and Zn were monitored by inductively coupled plasma mass spectrometry (ICP-MS). The potential ecological risk index method developed by Hakanson (1980) was employed to assess the potential risk of heavy-metal pollution. The potential ecological risk in the order of ER(Cd) > ER(Pb) > ER(Cu) > ER(Cr) > ER(Zn) have been obtained, which showed that Cd was the most important factor leading to risk. Based on the Cd pollution history, the cumulative acceleration and cumulative rate of Cd were estimated, then the fixed number of years exceeding the standard prediction model was established, which was used to predict the pollution trend of Cd under the accelerated accumulation mode and the uniform mode. Pearson correlation analysis and correspondence analysis are employed to identify the sources of heavy metals and the relationship between sampling points and variables. These findings provided some useful insights for making appropriate management strategies to prevent or decrease heavy-metal pollution around a coal gangue dump in the Yangcaogou coal mine and other similar areas elsewhere.

Among the major consequences of dam construction and operation are the deterioration of water quality and the increasing frequency of occurrence of harmful algae blooms in reservoirs and their tributaries. Former studies at Three Gorges Reservoir demonstrated that the Yangtze River main stream is the main source of nutrients and pollutants to connected tributary bays. Eutrophication and other water quality problems reported for the tributaries along Three Gorges Reservoir are likely a consequence of density-driven exchange flows. Past work has focused mainly on the influence of seasonal and daily flow regulation on exchange flows, less attention has been paid to hydrodynamic processes resulting from sub-daily discharge dynamics. High-frequency measurements of flow velocity and water level in a eutrophic tributary (Xiangxi River) of Three Gorges Reservoir revealed the persistent nature of bidirectional density currents within the bay. Superimposed on this mean flow, we observed ubiquitous flow oscillations with a period of approximately 2 h. The flow variations were associated with periodic water level fluctuations with increasing amplitude for increasing distance from the river mouth (up to ±0.1 m at a distance of 27.4 km from the river mouth). They were caused by a standing wave in the tributary bay, which was generated by rapid increase or decrease in discharge following peak-shaving operation modes at Three Gorges Dam. The high-frequency wave made up the largest contribution to the temporal variance of flow velocity in the tributary bay and represents a so far overlooked hydrodynamic feature of tributaries bays in large reservoirs.

Background Microorganisms serve important functions within numerous eukaryotic host organisms. An understanding of the variation in the plant niche-level microbiome, from rhizosphere soils to plant canopies, is imperative to gain a better understanding of how both the structural and functional processes of microbiomes impact the health of the overall plant holobiome. Using Populus trees as a model ecosystem, we characterized the archaeal/bacterial and fungal microbiome across 30 different tissue-level niches within replicated Populus deltoides and hybrid Populus trichocarpa × deltoides individuals using 16S and ITS2 rRNA gene analyses. Results Our analyses indicate that archaeal/bacterial and fungal microbiomes varied primarily across broader plant habitat classes (leaves, stems, roots, soils) regardless of plant genotype, except for fungal communities within leaf niches, which were greatly impacted by the host genotype. Differences between tree genotypes are evident in the elevated presence of two potential fungal pathogens, Marssonina brunnea and Septoria sp., on hybrid P. trichocarpa × deltoides trees which may in turn be contributing to divergence in overall microbiome composition. Archaeal/bacterial diversity increased from leaves, to stem, to root, and to soil habitats, whereas fungal diversity was the greatest in stems and soils. Conclusions This study provides a holistic understanding of microbiome structure within a bioenergy relevant plant host, one of the most complete niche-level analyses of any plant. As such, it constitutes a detailed atlas or map for further hypothesis testing on the significance of individual microbial taxa within specific niches and habitats of Populus and a baseline for comparisons to other plant species.

A unified hypoplastic model is formulated by incorporating the anisotropic critical state theory to describe the fabric effect in sand under both monotonic and cyclic loading conditions. An evolving deviatoric fabric tensor that characterizes the internal microstructure of sand is introduced into the hypoplastic model in conjunction with the intergranular strain concept. A scalar-valued fabric anisotropic variable indicating the interplay between the fabric and the loading direction is employed to account for the impact of fabric anisotropy on both the dilatancy and shear strength of sand. The model is demonstrated to be capable of simulating the anisotropic behavior of sand, using a single set of parameters under both monotonic and cyclic loading conditions, as evidenced by the satisfactory match with experimental results from various sources. In particular, by considering the influence of fabric evolution on the dilatancy of sand, the model adequately accounts for the fabric change effect and accurately captures the deviatoric strain accumulation, cyclic mobility, and the flow liquefaction phenomenon under cyclic loading condition.

In practical engineering, cyclic shear stresses induced by earthquakes, traffic, and waves are superimposed on the initial static shear stress in sand fills or deposits, leading to complex responses of soils such as their deformation characteristics, pore pressure generation, and susceptibility (or cyclic resistance) to liquefaction. To experimentally investigate the undrained cyclic response of saturated sand, a series of triaxial tests were performed, covering a broad range of initial static and cyclic deviatoric stress levels. The results indicate that different stress conditions lead to two types of cyclic behavior: cyclic mobility and residual deformation accumulation. The compressional static stress is beneficial to the cyclic resistance of the dense sand, whereas the extensional static stress is regarded as detrimental as it tended to reduce the cyclic strength. Moreover, by comparing the available test data obtained from the same sand with varying initial densities and confining pressures, the static shear effect on cyclic resistance was found to be dependent on the state of the sand. Compared to the interpretation made using the limiting pore pressure-based criterion, the conventional failure criterion using a cyclic axial strain of 5% may lead to a substantial overestimation of the cyclic resistance, thus resulting in unsafe assessment and design. Hence, by employing the pore pressure criterion, the pore pressure generated in the cyclic tests was investigated and was found to be significantly influenced by the static shear stress. A pore pressure generation model is proposed to obtain the pore pressure characteristics of sand under various static shear stress conditions.

Earlier, mapping of the 9p23–24 amplicon in esophageal cancer cell lines led us to the positional cloning of gene amplified in squamous cell carcinoma 1 ( GASC1 ), which encodes a nuclear protein with a Jumonji C domain that catalyzes lysine (K) demethylation of histones. However, the transforming roles of GASC1 in breast cancer remain to be determined. In this study, we identified GASC1 as one of the amplified genes for the 9p23–24 region in breast cancer, particularly in basal-like subtypes. The levels of GASC1 transcript expression were significantly higher in aggressive, basal-like breast cancers compared with nonbasal-like breast cancers. Our in vitro assays demonstrated that GASC1 induces transformed phenotypes, including growth factor-independent proliferation, anchorage-independent growth, altered morphogenesis in Matrigel, and mammosphere forming ability, when overexpressed in immortalized, nontransformed mammary epithelial MCF10A cells. Additionally, GASC1 demethylase activity regulates the expression of genes critical for stem cell self-renewal, including NOTCH1, and may be linked to the stem cell phenotypes in breast cancer. Thus, GASC1 is a driving oncogene in the 9p23–24 amplicon in human breast cancer and targeted inhibition of GASC1 histone demethylase in cancer could provide potential new avenues for therapeutic development.

Necroptosis is a caspase-independent form of regulated cell death executed by the receptor-interacting protein kinase 1 (RIP1), RIP3, and mixed lineage kinase domain-like protein (MLKL). Recently, necroptosis-based cancer therapy has been proposed to be a novel strategy for antitumor treatment. However, a big controversy exists on whether this type of therapy is feasible or just a conceptual model. Proponents believe that because necroptosis and apoptosis use distinct molecular pathways, triggering necroptosis could be an alternative way to eradicate apoptosis-resistant cancer cells. This hypothesis has been preliminarily validated by recent studies. However, some skeptics doubt this strategy because of the intrinsic or acquired defects of necroptotic machinery observed in many cancer cells. Moreover, two other concerns are whether or not necroptosis inducers are selective in killing cancer cells without disturbing the normal cells and whether it will lead to inflammatory diseases. In this review, we summarize current studies surrounding this controversy on necroptosis-based antitumor research and discuss the advantages, potential issues, and countermeasures of this novel therapy.