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Dielectric characterization of sugar mill wastewater and its impact on soil properties in the khadar and bangar regions
Benefit from huCAR19-IL18 cells in patients with CD19+ lymphomas after CAR T cells
Study on the triaxial compressive properties of alkali activated concrete after freeze-thaw cycles
Machine learning developed LKB1-AMPK signaling related signature for prognosis and drug sensitivity in hepatocellular carcinoma
The dominant synoptic patterns and basic characteristics of regional snowstorms in Northern Xinjiang over the past 70 years
Sex-based differences in the predictive significance of the waist circumference glucose index for future diabetes risk
Abstract Diabetes is a chronic metabolic disorder that has become a growing global health concern. Waist circumference-glucose index (WyG) is an effective predictor of diabetes; however, its predictive performance in the Japanese population and potential sex-specific differences remain unexplored. This study evaluated the dynamic prediction capability of WyG for diabetes in Japanese individuals, focusing on the differences between sexes. We analyzed data from 15,464 Japanese adults initially without diabetes (7,034 women and 8,430 men). Multivariate Cox regression analysis was used to evaluate the association between WyG and diabetes. Sex-based subgroup analyses were conducted to assess the impact of potential confounders. Sensitivity analysis was conducted to exclude specific populations to test for robustness, and E-values were calculated to evaluate the impact of unmeasured cofounders. Predictive performance was assessed using time-dependent receiver operating characteristic curve analysis. WyG was significantly associated with diabetes in both sexes. This association remained consistent across female subgroups, whereas in males, it was influenced by age and the presence of fatty liver. The area under the curve values ranged from 0.73 to 0.78 in women and 0.73 to 0.77 in men. Sex-specific thresholds (WyG > 8.19 for women, > 8.32 for men) were identified, with greater relative risk elevation for individuals above the threshold. WyG is a reliable predictor of diabetes, with its predictive performance varying across sexes.
High-intensity light disrupts intracellular organelle dynamics via microtubule depolymerization
Temperature and CO2 concentration in honey bee hives exhibit circadian rhythms
Abstract Worker honey bees exhibit circadian rhythms with respect to locomotor activity but circadian analyses have seldom been applied to colony-level behavior. Circadian rhythms have been defined as having three main characteristics: a period of approximately 24 h maintained in the absence of external cues; a period maintained over a range of temperatures; and a phase fixed by external cues from the environment. In this study honey bee colonies were subjected to two kinds of light regimes at 5 °C in a cold storage unit (CSU): (1) constant darkness; and (2) after 6–12 d constant darkness, 12 h light exposure from 6PM to 6AM (i.e. a phase approximately 12 h offset from ambient conditions). Periodogram analyses of data from the 1st light regime showed that temperature and CO2 concentration had stable 24 h periods after 20 d, as was observed for colonies in warmer temperatures in outside conditions. Period strength of temperature decreased over time in the CSU but not CO2. Cosinor analyses of data from the 2nd light regime showed a temperature phase change of about 9 h 37 min between the end of the CSU period, after 28–33 d in light regime, and after 7–12 d in outdoor conditions in the post-CSU period. The same comparison for CO2 concentration showed a phase change of about 11 h 55 min. These data indicated honey bee colonies produced circadian rhythms in hive temperature and CO2 concentration with periods both present in the absence of external cues, and with phases that can be driven by light. Rhythms associated with CO2 concentration changed with respect to light treatment more than rhythms associated with hive temperature. Based on data from longer-term (60 d) experiments, daily rhythm phases and day lengths differed significantly between hive temperature and CO2 after 15 d in the 12 l:12D light regime, and remained so in outdoor conditions.
Human burials indicate climate-mediated shifts in South African agriculturalist demography after 2000 years ago
Abstract South Africa’s Iron Age (c. 250 CE – 1850 CE) was a period of socio-economic transitions. With the spread of Bantu-speaking peoples from western Africa, the region saw the development of settled agriculturalist societies, the rise of complex chiefdoms, and the development of early states such as Mapungubwe. Questions about how settlements and demographics were influenced by environmental factors are central to the study of this period. Climatic conditions directly impact carrying capacity and agricultural productivity. It is therefore likely that climate variability was an important factor in the success of farming communities, determining food security, population movements, and settlement expansions or abandonments. In this paper we focus on northeastern South Africa and employ the frequency of archaeological human burials and highly resolved palaeoclimate records to assess the relationship between population dynamics and climate change. This reveals significant subregional variability in both human burial frequency and climate change across the subcontinent. Within the subregions, burial frequency shows a positive correlation with humidity, indicating that climatic factors played a pivotal role in shaping the pattern and size of settlements during this period.
Deep learning based predictive models for real time accident prevention in autonomous vehicle networks
Tumour and microenvironment crosstalk in NSCLC progression and response to therapy
Correction for Smith et al., A twist grain boundary phase in aqueous solutions of the nucleic acid tetramer GTAC
Metagenomics reveals functional profiles of gut microbiota during the recovery phase of acute pancreatitis
Unravelling the luminescence spectrum of novel ceramic nucleus cultured pearl and the cause of its strong luster
A technique to reduce the probability of band-to-band tunneling for eliminating injected minority carriers in nano scale field-effect diode
On the limits of the intervention on complex systems guided by functional networks
Abstract Complex networks, and functional networks in particular, have become a standard tool to understand the structure and dynamics of real-world complex systems. One usually hidden assumption is that the structure of the reconstructed functional networks encodes useful information to guide interventions on the physical layer, when the latter is not known. We here test this assumption using a minimal model, simulating a propagation process in a physical network, and guiding interventions using node properties observed in the corresponding functional representation. We show how this approach becomes less optimal the more complex the topology is; up to becoming marginally better than choosing nodes at random in the real case of the European air transport network.