Genomic insights into the formation of human populations in East Asia.

The deep population history of East Asia remains poorly understood owing to a lack of ancient DNA data and sparse sampling of present-day people1,2. Here we report genome-wide data from 166 East Asian individuals dating to between 6000 BC and AD 1000 and 46 present-day groups. Hunter-gatherers from Japan, the Amur River Basin, and people of Neolithic and Iron Age Taiwan and the Tibetan Plateau are linked by a deeply splitting lineage that probably reflects a coastal migration during the Late Pleistocene epoch. We also follow expansions during the subsequent Holocene epoch from four regions. First, hunter-gatherers from Mongolia and the Amur River Basin have ancestry shared by individuals who speak Mongolic and Tungusic languages, but do not carry ancestry characteristic of farmers from the West Liao River region (around 3000 BC), which contradicts theories that the expansion of these farmers spread the Mongolic and Tungusic proto-languages. Second, farmers from the Yellow River Basin (around 3000 BC) probably spread Sino-Tibetan languages, as their ancestry dispersed both to Tibet-where it forms approximately 84% of the gene pool in some groups-and to the Central Plain, where it has contributed around 59-84% to modern Han Chinese groups. Third, people from Taiwan from around 1300 BC to AD 800 derived approximately 75% of their ancestry from a lineage that is widespread in modern individuals who speak Austronesian, Tai-Kadai and Austroasiatic languages, and that we hypothesize derives from farmers of the Yangtze River Valley. Ancient people from Taiwan also derived about 25% of their ancestry from a northern lineage that is related to, but different from, farmers of the Yellow River Basin, which suggests an additional north-to-south expansion. Fourth, ancestry from Yamnaya Steppe pastoralists arrived in western Mongolia after around 3000 BC but was displaced by previously established lineages even while it persisted in western China, as would be expected if this ancestry was associated with the spread of proto-Tocharian Indo-European languages. Two later gene flows affected western Mongolia: migrants after around 2000 BC with Yamnaya and European farmer ancestry, and episodic influences of later groups with ancestry from Turan.

A Miniaturized Colorimeter with a Novel Design and High Precision for Photometric Detection.

Water quality detection plays an increasingly important role in environmental protection. In this work, a novel colorimeter based on the Beer-Lambert law was designed for chemical element detection in water with high precision and miniaturized structure. As an example, the colorimeter can detect phosphorus, which was accomplished in this article to evaluate the performance. Simultaneously, a modified algorithm was applied to extend the linear measurable range. The colorimeter encompassed a near infrared laser source, a microflow cell based on microfluidic technology and a light-sensitive detector, then Micro-Electro-Mechanical System (MEMS) processing technology was used to form a stable integrated structure. Experiments were performed based on the ammonium molybdate spectrophotometric method, including the preparation of phosphorus standard solution, reducing agent, chromogenic agent and color reaction. The device can obtain a wide linear response range (0.05 mg/L up to 7.60 mg/L), a wide reliable measuring range up to 10.16 mg/L after using a novel algorithm, and a low limit of detection (0.02 mg/L). The size of flow cell in this design is 18 mm × 2.0 mm × 800 µm, obtaining a low reagent consumption of 0.004 mg ascorbic acid and 0.011 mg ammonium molybdate per determination. Achieving these advantages of miniaturized volume, high precision and low cost, the design can also be used in automated in situ detection.

Betulinic Acid and its Derivatives as Potential Antitumor Agents.

Betulinic acid (BA) is a lupane-type pentacyclic triterpene, distributed ubiquitously throughout the plant kingdom. BA and its derivatives demonstrate multiple bioactivities, particularly an antitumor effect. This review critically describes the recent research on isolation, synthesis, and derivatization of BA and its natural analogs betulin and 23-hydroxybetulinic acid. The subsequent part of the review focuses on the current knowledge of antitumor properties, combination treatments, and pharmacological mechanisms of these compounds. A 3D-QSAR analysis of 62 BA derivatives against human ovarian cancer A2780 is also included to provide information concerning the structure-cytotoxicity relationships of these compounds.

Synthesis of new ent-labdane diterpene derivatives from andrographolide and evaluation on cytotoxic activities.

There are many reports for andrographolide modification regarding antitumor effects. Transformation of the five-membered lactone ring to furan aromatic ring still results in compounds with good cytotoxicity. To determine further the importance of the five-membered lactone ring and to obtain better lead compounds, we transformed the five-membered lactone ring in andrographolide. New types of ent-labdane diterpene derivatives were made, whose cytotoxic activities were measured in vitro. Preliminary SAR was summarized and two compounds, 7 and 26, with good cytotoxic activity were obtained, which have the potential to be developed into new antitumor drugs.

Automatic detection of sleep apnea based on EEG detrended fluctuation analysis and support vector machine.

Sleep apnea syndrome (SAS) is prevalent in individuals and recently, there are many studies focus on using simple and efficient methods for SAS detection instead of polysomnography. However, not much work has been done on using nonlinear behavior of the electroencephalogram (EEG) signals. The purpose of this study is to find a novel and simpler method for detecting apnea patients and to quantify nonlinear characteristics of the sleep apnea. 30 min EEG scaling exponents that quantify power-law correlations were computed using detrended fluctuation analysis (DFA) and compared between six SAS and six healthy subjects during sleep. The mean scaling exponents were calculated every 30 s and 360 control values and 360 apnea values were obtained. These values were compared between the two groups and support vector machine (SVM) was used to classify apnea patients. Significant difference was found between EEG scaling exponents of the two groups (p < 0.001). SVM was used and obtained high and consistent recognition rate: average classification accuracy reached 95.1% corresponding to the sensitivity 93.2% and specificity 98.6%. DFA of EEG is an efficient and practicable method and is helpful clinically in diagnosis of sleep apnea.

Protecting primary teeth from dental erosion through bioactive glass.

OBJECTIVES: The present study aimed to evaluate the effectiveness of bioactive glass (BAG) in preventing dental erosion in primary teeth. METHODS: Enamel and dentin specimens (2 × 2 × 2 mm) were obtained from extracted primary teeth, which were randomly divided into the following groups based on the pretreatments (n = 12): DW (deionized water), NaF (2 % sodium fluoride), 2BAG (2 % BAG), 4BAG (4 % BAG), 6BAG (6 % BAG), and 8BAG (8 % BAG). The specimens were immersed in the respective solutions for 2 min and subjected to in vitro erosive challenges (4 × 5 min/d) for 5 d. The erosive enamel loss (EEL), erosive dentin loss (EDL), and the thickness of the demineralized organic matrix (DOM) were measured using a contact profilometer. The surface microhardness (SMH) was measured, and the percentage of SMH loss (%SMHL) was calculated. The surface morphology and mineral composition were evaluated by scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS), respectively. RESULTS: After the erosive challenges, the EEL, EDL, and%SMHL of the 2BAG, 4BAG, 6BAG, and 8BAG groups significantly reduced, with the greatest reduction was observed in the 6BAG (EEL: 6.5 ± 0.2 µm;%SMHL in enamel: 12.8 ± 2.6; EDL: 7.9 ± 0.3 µm; %SMHL in dentin: 22.1 ± 2.7) and 8BAG groups (EEL: 6.4 ± 0.4 µm;%SMHL in enamel: 11.0 ± 1.9; EDL: 7.8 ± 0.5 µm; %SMHL in dentin: 22.0 ± 2.5) (P < 0.05). With increasing BAG concentrations, the number of surface deposits containing Ca, P, and Si increased. CONCLUSIONS: 6BAG was the most effective for preventing dental erosion in primary teeth and showed a particularly strong potential for dentin erosion prevention. CLINICAL SIGNIFICANCE: Bioactive glass, especially at a 6 % concentration, has proven effective in reducing erosive tooth wear and surface microhardness loss while also protecting demineralized organic matrix in primary dentin.

Polarized Tunneling Transistor for Ultralow-Energy-Consumption Artificial Synapse toward Neuromorphic Computing.

Neural networks based on low-power artificial synapses can significantly reduce energy consumption, which is of great importance in today's era of artificial intelligence. Two-dimensional (2D) material-based floating-gate transistors (FGTs) have emerged as compelling candidates for simulating artificial synapses owing to their multilevel and nonvolatile data storage capabilities. However, the low erasing/programming speed of FGTs renders them unsuitable for low-energy-consumption artificial synapses, thereby limiting their potential in high-energy-efficient neuromorphic computing. Here, we introduce a FGT-inspired MoS2/Trap/PZT heterostructure-based polarized tunneling transistor (PTT) with a simple fabrication process and significantly enhanced erasing/programming speed. Distinct from the FGT, the PTT lacks a tunnel layer, leading to a marked improvement in its erasing/programming speed. The PTT's highest erasing/programming (operation) speed can reach ∼20 ns, which outperforms the performance of most FGTs based on 2D heterostructures. Furthermore, the PTT has been utilized as an artificial synapse, and its weight-update energy consumption can be as low as 0.0002 femtojoule (fJ), which benefits from the PTT's ultrahigh operation speed. Additionally, PTT-based artificial synapses have been employed in constructing artificial neural network simulations, achieving facial-recognition accuracy (95%). This groundbreaking work makes it possible for fabricating future high-energy-efficient neuromorphic transistors utilizing 2D materials.

A comparison of the performances of an artificial neural network and a regression model for GFR estimation.

BACKGROUND: Accurate estimation of glomerular filtration rate (GFR) is important in clinical practice. Current models derived from regression are limited by the imprecision of GFR estimates. We hypothesized that an artificial neural network (ANN) might improve the precision of GFR estimates. STUDY DESIGN: A study of diagnostic test accuracy. SETTING & PARTICIPANTS: 1,230 patients with chronic kidney disease were enrolled, including the development cohort (n=581), internal validation cohort (n=278), and external validation cohort (n=371). INDEX TESTS: Estimated GFR (eGFR) using a new ANN model and a new regression model using age, sex, and standardized serum creatinine level derived in the development and internal validation cohort, and the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration) 2009 creatinine equation. REFERENCE TEST: Measured GFR (mGFR). OTHER MEASUREMENTS: GFR was measured using a diethylenetriaminepentaacetic acid renal dynamic imaging method. Serum creatinine was measured with an enzymatic method traceable to isotope-dilution mass spectrometry. RESULTS: In the external validation cohort, mean mGFR was 49±27 (SD) mL/min/1.73 m2 and biases (median difference between mGFR and eGFR) for the CKD-EPI, new regression, and new ANN models were 0.4, 1.5, and -0.5 mL/min/1.73 m2, respectively (P<0.001 and P=0.02 compared to CKD-EPI and P<0.001 comparing the new regression and ANN models). Precisions (IQRs for the difference) were 22.6, 14.9, and 15.6 mL/min/1.73 m2, respectively (P<0.001 for both compared to CKD-EPI and P<0.001 comparing the new ANN and new regression models). Accuracies (proportions of eGFRs not deviating >30% from mGFR) were 50.9%, 77.4%, and 78.7%, respectively (P<0.001 for both compared to CKD-EPI and P=0.5 comparing the new ANN and new regression models). LIMITATIONS: Different methods for measuring GFR were a source of systematic bias in comparisons of new models to CKD-EPI, and both the derivation and validation cohorts consisted of a group of patients who were referred to the same institution. CONCLUSIONS: An ANN model using 3 variables did not perform better than a new regression model. Whether ANN can improve GFR estimation using more variables requires further investigation.

Estimation of glomerular filtration rate by a radial basis function neural network in patients with type-2 diabetes mellitus.

BACKGROUND: Accurate and precise estimates of glomerular filtration rate (GFR) are essential for clinical assessments, and many methods of estimation are available. We developed a radial basis function (RBF) network and assessed the performance of this method in the estimation of the GFRs of 207 patients with type-2 diabetes and CKD. METHODS: Standard GFR (sGFR) was determined by (99m)Tc-DTPA renal dynamic imaging and GFR was also estimated by the 6-variable MDRD equation and the 4-variable MDRD equation. RESULTS: Bland-Altman analysis indicated that estimates from the RBF network were more precise than those from the other two methods for some groups of patients. However, the median difference of RBF network estimates from sGFR was greater than those from the other two estimates, indicating greater bias. For patients with stage I/II CKD, the median absolute difference of the RBF network estimate from sGFR was significantly lower, and the P50 of the RBF network estimate (n = 56, 87.5%) was significantly higher than that of the MDRD-4 estimate (n = 49, 76.6%) (p < 0.0167), indicating that the RBF network estimate provided greater accuracy for these patients. CONCLUSIONS: In patients with type-2 diabetes mellitus, estimation of GFR by our RBF network provided better precision and accuracy for some groups of patients than the estimation by the traditional MDRD equations. However, the RBF network estimates of GFR tended to have greater bias and higher than those indicated by sGFR determined by (99m)Tc-DTPA renal dynamic imaging.

[Pseudo-accommodation with accommodating intraocular lens in patients at different ages].

OBJECTIVE: To compare the clinical performances of patients in different ages with implantation of a accommodating IOLs. METHODS: It was a retrospective study. Forty-seven eyes (47 patients) were enrolled in 3 groups for phacoemulsification and a accommodating IOL implantation. According to their ages, they were divided into 3 groups: ≤ 45 years, 46 - 59 years, and ≥ 60 years. Parameters analyzed after more than 3 months postoperation were uncorrected distance, best-corrected distance, uncorrected near, and distance-corrected near visual acuities; changes of anterior chamber depth(ACD) during accommodative measured using the ultrasound biomicroscopy (UBM);changes of ACD by instilling 2% pilocarpine using the A-ultrasonic scan; and the amplitude of accommodation using the pushing-up test. RESULTS: No significant difference was observed between distance and near visual acuities of IOL groups. The mean changes of ACD measured with UBM in the group of ≤ 45 years [(0.16 ± 0.12) mm] was significantly higher than the other age groups [46 - 59 years, (0.06 ± 0.06) mm, P = 0.00; ≥ 60 years, (0.07 ± 0.05) mm, P = 0.008)]. The mean changes of ACD stimulated by pilocarpine measured with A-ultrasonic scan in the group of ≥ 60 years [(0.17 ± 0.14) mm] was significantly lower than the other age groups [≤ 45 years, (0.68 ± 0.44) mm, P = 0.00; 46 - 59 years, (0.43 ± 0.20) mm, P = 0.00]. The accommodative amplitude of the ≥ 60 years groups ((2.32 ± 0.88) D) was lower than the group of ≤ 45 years [(2.87 ± 0.52) D, P = 0.005]. CONCLUSIONS: The accommodative amplitude of patients implanted with accommodating IOLs stepped down following the increase of age. However, no statistical differences were found in distance and near visual acuities between the different age groups.