Liquid-Liquid Phase Separation in Single Suspended Aerosol Microdroplets

Liquid-liquid phase separation (LLPS) is ubiquitous in ambient aerosols. This specific morphology exerts substantial impacts on the physicochemical properties and atmospheric processes of aerosols, particularly on the gas-particle mass transfer, the interfacial heterogeneous reaction, and the surface albedo. Although there are many studies on the LLPS of aerosols, a clear picture of LLPS in individual aerosols is scarce due to the experimental difficulties of trapping a single particle and mimicking the suspended state of real aerosols. Here, we investigate the phase separation in individual contactless microdroplets by a self-constructed laser tweezer/Raman spectroscopy system. The dynamic transformation of the morphology of optically trapped droplets over the course of humidity cycles is detected by the time-resolved cavity-enhanced Raman spectra. The impacts of pH and inorganic components on LLPS in aerosols are discussed. The results show that the increasing acidity can enhance the miscibility between the hydrophilic and hydrophobic phases and decrease the separation relative humidity of aerosols. Moreover, the inorganic components also have various impacts on the aerosol phase state, whose influence depends on their different salting-out capabilities. It brings possible implications on the morphology of actual atmospheric particles, particularly for those dominated by internal mixtures of inorganic and organic components.

Sub-Cellular Dynamic Analysis of BGC823 Cells after Treatment with the Multi-Component Drug CKI Using Raman Spectroscopy

Multi-component drugs (MCDs) can induce various cellular changes covering multiple levels, from molecular and subcellular structure to cell morphology. A "non-invasive" method for comprehensively detecting the dynamic changes of cellular fine structure and chemical components on the subcellular level is highly desirable for MCD studies. In this study, the subcellular dynamic processes of gastric cancer BGC823 cells after treatment with a multi-component drug, Compound Kushen Injection (CKI), were investigated using a homemade, high-resolution, confocal Raman spectroscopy (RS) device combined with bright-field imaging. The Raman spectra of the nucleus, cytoplasm and intracellular vesicles (0.4-1 μm) were collected simultaneously for each cell treated with CKI at different times and doses. The RS measurements showed that CKI decreased the DNA signatures, which the drug is known to inhibit. Meanwhile, the CKI-induced subcellular dynamic changes in the appearance of numerous intracellular vesicles and the deconstruction of cytoplasm components were observed and discussed. The results demonstrated that high-resolution subcellular micro-Raman spectroscopy has potential for detecting fine cellular dynamic variation induced by drugs and the screening of MCDs in cancer therapy.

Measurement of atmospheric nanoparticles: Bridging the gap between gas-phase molecules and larger particles

Atmospheric nanoparticles are crucial components contributing to fine particulate matter (PM_2.5), and therefore have significant effects on visibility, climate, and human health. Due to the unique role of atmospheric nanoparticles during the evolution process from gas-phase molecules to larger particles, a number of sophisticated experimental techniques have been developed and employed for online monitoring and characterization of the physical and chemical properties of atmospheric nanoparticles, helping us to better understand the formation and growth of new particles. In this paper, we firstly review these state-of-the-art techniques for investigating the formation and growth of atmospheric nanoparticles (e.g., the gas-phase precursor species, molecular clusters, physicochemical properties, and chemical composition). Secondly, we present findings from recent field studies on the formation and growth of atmospheric nanoparticles, utilizing several advanced techniques. Furthermore, perspectives are proposed for technique development and improvements in measuring atmospheric nanoparticles.

Rapid and accurate identification of pathogenic bacteria at the single-cell level using laser tweezers Raman spectroscopy and deep learning

We report a new method for the rapid identification of pathogenic bacterial species at the single-cell level that combines laser tweezers Raman spectroscopy (LTRS) with deep learning (DL). LTRS can accurately measure single-cell Raman spectra (scRS) without destroying and labeling cells. Based on the scRS data, DL rapidly and accurately identifies pathogenic bacteria. We measured scRS of 15 species bacteria using homemade LTRS. For each species, approximately, 160 cells from three different patients were measured, one patient's data were used as test set, and the rest after being augmented was used as training set. A residual network (ResNet) model, trained on the augmented training set, achieved an accuracy of 94.53% on the test set. Moreover, we applied gradient-weighted class activation mapping to visualize the proposed model. Finally, we demonstrated the advantages of ResNet over traditional machine-learning algorithms.

Correction: Fast label-free recognition of NRBCs by deep-learning visual object detection and single-cell Raman spectroscopy

Correction for 'Fast label-free recognition of NRBCs by deep-learning visual object detection and single-cell Raman spectroscopy' by Teng Fang et al., Analyst, 2022, https://doi.org/10.1039/D2AN00024E.

The relative humidity-dependent viscosity of single quasi aerosol particles and possible implications for atmospheric aerosol chemistry

Viscosity is a fundamental physicochemical property of aerosol particles that influences chemical evolution, mass transfer rates, particle formation, etc. and also changes with ambient relative humidity (RH). However, the viscosity of real individual aerosol particles still remains less understood. Here, we developed a novel optical system based on dual optical tweezers to measure the viscosity of single suspending aerosol droplets under different RH conditions. In our experiment, a pair of quasi atmospheric aerosol droplets composed of organic and inorganic chemical substances were trapped and levitated by dual laser beams, respectively, and then collided and coalesced. The backscattering light signals and bright-field images of the dynamic coalescence process were recorded to infer the morphological relaxation time and the diameter of the composited droplet. Then, the viscosity of the droplet was calculated based on these measured values. The ambient RH of the aerosol droplets was controlled by varying the relative flow rates of dry and humidified nitrogen gas in a self-developed aerosol chamber. The viscosities of single aqueous droplets nebulized with solutes of sucrose, various sulfates and nitrates, and organic/inorganic mixtures were measured over the atmospheric RH range. Besides, the viscosities of the proxies of actual ambient aerosols in Beijing were investigated, which reasonably interpreted the aerosol chemistry transforming from sulfate dominating to nitrate dominating at the PM₁₀ (particulate matter with an aerodynamic diameter of less than 10 μm) level in the last decade in Beijing. Furthermore, the hygroscopicity of droplets with a solute of organic/inorganic mixtures was researched to obtain a deep insight into the relationship between the viscosity and mass transfer process. Hence, we provide a robust approach for investigating the viscosity and hygroscopicity of the actual individual liquid PM₁₀ aerosols.

RamanNet: a lightweight convolutional neural network for bacterial identification based on Raman spectra

Raman spectroscopy combined convolutional neural network (CNN) enables rapid and accurate identification of the species of bacteria. However, the existing CNN requires a complex hyperparameters model design. Herein, we propose a new simple network architecture with less hyperparameter design and low computation cost, RamanNet, for rapid and accurate identifying of bacteria at the species level based on its Raman spectra. We verified that compared with the previous CNN methods, the RamanNet reached comparable results on the Bacteria-ID Raman spectral dataset and PKU-bacterial Raman spectral datasets, but using only about 1/45 and 1/297 network parameters, respectively. RamanNet achieved an average isolate-level accuracy of 84.7 ± 0.3%, antibiotic treatment identification accuracy of 97.1 ± 0.3%, and distinguished accuracy of 81.6 ± 0.9% for methicillin-resistant and -susceptible Staphylococcus aureus (MRSA and MSSA) on the Bacteria-ID dataset, respectively. Moreover, it achieved an average accuracy of 96.04% on the PKU-bacterial dataset. The RamanNet model benefited from fewer model parameters that can be quickly trained even using CPU. Therefore, our method has the potential to rapidly and accurately identify bacterial species based on their Raman spectra and can be easily extended to other classification tasks based on Raman spectra.

We propose a novel CNN model named RamanNet for rapid and accurate identification of bacteria at the species-level based on Raman spectra. Compared to previous CNN methods, the RamanNet reached comparable results on the Bacteria-ID Raman spectral dataset.

Fast label-free recognition of NRBCs by deep-learning visual object detection and single-cell Raman spectroscopy

A computer-assisted and label-free method to quickly recognize the rare nucleated red blood cells by combining visual object detection with single-cell Raman spectroscopy.

Single-Cell Multimodal Analytical Approach by Integrating Raman Optical Tweezers and RNA Sequencing

Single-cell analysis has become a state-of-art approach to heterogeneity profiling in tumor cells. Herein, we realize a kind of single-cell multimodal analytical approach by combining single-cell RNA sequencing (scRNA-seq) with Raman optical tweezers (ROT), a label-free single-cell identification and isolation technique, and apply it to investigate drug sensitivity. The drug sensitivity of human BGC823 gastric cancer cells toward different drugs, paclitaxel and sodium dichloroacetate, was distinguished in the conjoint analytical way including morphology monitoring, Raman identification, and transcriptomic profiling. Each individual BGC823 cancer cell was measured by Raman spectroscopy, then nondestructively isolated out by ROT, and finally RNA-sequenced. Our results demonstrate each analytical mode can reflect cell response to the drugs from different perspectives and is consistent and complementary with each other. Therefore, we believe the multimodal analytical approach offers an access to comprehensive characterizations of the unicellular complexity, which especially makes sense for studying tumor heterogeneity or a desired special cell from a mixture cell sample such as whole blood.

Rapid and accurate identification of marine microbes with single-cell Raman spectroscopy

Rapid and accurate identification of individual microorganisms, such as pathogenic or unculturable microbes, is significant in microbiology. In this work, rapid identification of marine microorganisms by single-cell Raman spectroscopy (scRS) using one-dimensional convolutional neural networks (1DCNN) was explored. Here, single-cell Raman spectra of ten species of marine actinomycetes, two species of non-marine actinomycetes and E. coli (as a reference) were individually collected. Several common classification algorithms in chemometrics, including linear discriminant analysis with principal component analysis and a support vector machine, were applied to evaluate the 1DCNN performance based on the raw and pre-processed Raman spectra. 1DCNN showed superior performance on the raw data in terms of its accuracy and recall rate compared with other classification algorithms. Our investigation demonstrated that the scRS-integrating advanced 1DCNN classification algorithm provided a rapid and accurate approach for identifying individual microorganisms without time-consuming cell culture and sophisticated or specific techniques, which could be a useful methodology for discriminating the microbes that cannot be cultured under normal conditions, especially for 'biological risk'-related emergencies.

Nondestructive Identification and Accurate Isolation of Single Cells through a Chip with Raman Optical Tweezers

Raman optical tweezers (ROT) as a label-free technique plays an important role in single-cell study such as heterogeneity of tumor and microbial cells. Herein we designed a chip utilizing ROT to isolate a specific single cell. The chip was made from a polydimethylsiloxane (PDMS) slab and formed into a gourd-shaped reservoir with a connected channel on a cover glass. On the chip an individual cell could be isolated from a cell crowd and then extracted with ∼0.5 μL of phosphate-buffered saline (PBS) via pipet immediately after Raman spectral measurements of the same cell. As verification, we separated four different type of cells including BGC823 gastric cancer cells, erythrocytes, lymphocytes, and E. coli cells and quantifiably characterized the heterogeneity of the cancer cells, leukocyte subtype, and erythrocyte status, respectively. The average time of identifying and isolating a specific cell was 3 min. Cell morphology comparison and viability tests showed that the successful rate of single-cell isolation was about 90%. Thus, we believe our platform could further couple other single-cell techniques such as single-cell sequencing and become a multiperspective analytical approach at the level of a single cell.

Laser trapping of Ag nanoparticles to enhance Raman spectroscopy in aqueous media

Laser trapping (LT) of metallic nanoparticles (NPs) is an approach that has the potential to enhance Raman spectroscopy in aqueous media. In this paper, we report the LT of multiple 60-nm Ag NPs using a tightly focused 1064-nm Gaussian laser beam. The dynamic process (trapping and escaping) of the individual Ag NPs were recorded using a charge coupled device (CCD) camera in backscattering illumination mode. We found that up to four Ag NPs could be simultaneously trapped; however, they were unstable in the laser trap due to Brownian motion and NP-NP interactions. However, after mixing Ag NPs with Bacillus subtilis, more of the Ag NPs could be trapped together with the bacteria. Furthermore, a 532-nm solid-state laser beam was used to activate Raman scattering of the Ag NPs + Bacillus subtilis sample. Based on repetitive measurements, the Raman spectra of the Ag NPs + Bacillus subtilis sample were enhanced and the results were consistent. Our work suggests that LT of metallic NPs can be used to enhance Raman spectroscopy in aqueous media. We believe that the enhanced Raman spectroscopy will be useful for real-time biological assays.

Dynamic characterization of drug resistance and heterogeneity of the gastric cancer cell BGC823 using single-cell Raman spectroscopy

Drug resistance and heterogeneous characteristics of human gastric carcinoma cells (BGC823) under the treatment of paclitaxel (PTX) were investigated using single-cell Raman spectroscopy (RS). RS of normal and drug-resistant BGC823 cells (DR-BGC823) were collected and analyzed using arithmetic, statistic and individual spectrum analysis. The dynamic effects of paclitaxel (PTX) in normal and DR-BGC823 cells were evaluated dynamically. The RS intensity changed with PTX over time and produced distinct different results for the two types of cells. The average RS intensities of the normal BGC823 cells initially decreased and then increased under PTX treatment after 24 hours. In contrast, upon exposure to PTX, the average intensity of the DR-BGC823 cells initially increased within 12 hours and then gradually decreased and approached a steady state. The temporal variation of the typical component in the cells was analyzed by comparing the ratios between Raman bands. More importantly, the heterogeneous characteristics of the BGC823 cells under PTX treatment were quantified and clustered using hierarchical trees combined with RS intensity changes. The 'outlier' cells related to drug resistance were discriminated. The heterogeneity of the normal BGC823 cells under drug treatment gradually appeared over time, and was evaluated with the eigenvalues of principal component analysis (PCA). Our study indicates that single-cell RS may be useful in systematically and dynamically characterizing the drug response of cancer cells at the single-cell level.

Anti-Cancer Drug Sensitivity Assay with Quantitative Heterogeneity Testing Using Single-Cell Raman Spectroscopy

A novel anti-cancer drug sensitivity testing (DST) approach was developed based on in vitro single-cell Raman spectrum intensity (RSI). Generally, the intensity of Raman spectra (RS) for a single living cell treated with drugs positively relates to the sensitivity of the cells to the drugs. In this study, five cancer cell lines (BGC 823, SGC 7901, MGC 803, AGS, and NCI-N87) were exposed to three cytotoxic compounds or to combinations of these compounds, and then they were evaluated for their responses with RSI. The results of RSI were consistent with conventional DST methods. The parametric correlation coefficient for the RSI and Methylthiazolyl tetrazolium assay (MTT) was 0.8558 ± 0.0850, and the coefficient of determination was calculated as R² = 0.9529 ± 0.0355 for fitting the dose⁻response curve. Moreover, RSI data for NCI-N87 cells treated by trastuzumab, everolimus (cytostatic), and these drugs in combination demonstrated that the RSI method was suitable for testing the sensitivity of cytostatic drugs. Furthermore, a heterogeneity coefficient H was introduced for quantitative characterization of the heterogeneity of cancer cells treated by drugs. The largest possible variance between RSs of cancer cells were quantitatively obtained using eigenvalues of principal component analysis (PCA). The ratio of H between resistant cells and sensitive cells was greater than 1.5, which suggested the H-value was effective to describe the heterogeneity of cancer cells. Briefly, the RSI method might be a powerful tool for simple and rapid detection of the sensitivity of tumor cells to anti-cancer drugs and the heterogeneity of their responses to these drugs.

Preconception antiphospholipid antibodies and risk of subsequent early pregnancy loss

Objectives To prospectively estimate the association of preconception antiphospholipid antibodies (aPL) with subsequent pregnancy loss using a cohort design. aPL have been associated with recurrent early pregnancy loss (EPL) prior to 10 weeks in previous case-control studies. Prospective ascertainment of pregnancy loss is challenging, as most women do not seek care prior to EPL. Methods Secondary analysis of the Effects of Aspirin in Gestation and Reproduction trial of preconception low-dose aspirin. Preconception anticardiolipin (aCL) and anti-β2-glycoprotein-I (a-β2-I) were assessed in 1208 women with one or two prior pregnancy losses and no more than two prior live births. Comparison cohorts were defined by positive aPL (+aPL) or negative aPL (-aPL) status. All women were followed for six menstrual cycles while trying to conceive; if successful, they underwent an ultrasound at 6-7 weeks' gestation. EPL was defined as loss prior to 10 weeks' gestation; embryonic loss was loss after visualization of an embryo but prior to 10 weeks; clinical loss was any loss after visualization of an embryo (with or without fetal cardiac activity detected). Results In total, 14/1208 (1%) tested positive for +aPL. 786/1208 (65%) women had positive human chorionic gonadotropin during the study period, of which 9/786 (1%) had +aPL. Of the 786 pregnant women, 589 (75%) had live births and 24% had pregnancy losses. Women with +aPL experienced EPL at similar rates as women with -aPL, 44% vs 21% (aRR 2.4, 95% confidence interval (CI) 0.5-10.9). Embryonic loss was more common in women with +aCL IgM (aRR 4.8, 95% CI 1.0-23.0) and in women with two positive aPL. Clinical pregnancy loss was more common in women with positive a-β2-I IgM (50% vs 16.5%, aRR 3.7, 95% CI 1.3-10.8). Conclusion Positive levels of aPL are rare in women with one or two prior pregnancy losses and are not clearly associated with an increased rate of subsequent loss. Clinical trial registration The original source study was registered at ClinicalTrials.gov (#NCT00467363).

Piconewton-Scale Analysis of Ras-BRaf Signal Transduction with Single-Molecule Force Spectroscopy

Intermolecular interactions dominate the behavior of signal transduction in various physiological and pathological cell processes, yet assessing these interactions remains a challenging task. Here, this study reports a single-molecule force spectroscopic method that enables functional delineation of two interaction sites (≈35 pN and ≈90 pN) between signaling effectors Ras and BRaf in the canonical mitogen-activated protein kinase (MAPK) pathway. This analysis reveals mutations on BRaf at Q257 and A246, two sites frequently linked to cardio-faciocutaneous syndrome, result in ≈10-30 pN alterations in RasBRaf intermolecular binding force. The magnitude of changes in RasBRaf binding force correlates with the size of alterations in protein affinity and in α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-sensitive glutamate receptor (-R)-mediated synaptic transmission in neurons expressing replacement BRaf mutants, and predicts the extent of learning impairments in animals expressing replacement BRaf mutants. These results establish single-molecule force spectroscopy as an effective platform for evaluating the piconewton-level interaction of signaling molecules and predicting the behavior outcome of signal transduction.

Associations between urinary phthalate concentrations and semen quality parameters in a general population

STUDY QUESTION

Are urinary phthalate concentrations associated with altered semen quality parameters among males recruited from the general population?

SUMMARY ANSWER

Urinary levels of metabolites of phthalate diesters are associated with lower total sperm counts, larger sperm head sizes, and higher percentages of morphologically abnormal sperm.

WHAT IS KNOWN ALREADY

High dose experiments in rats implicate phthalates as anti-androgens. Studies involving infertile men seeking care suggest that phthalates influence measures of semen quality raising concern about the implications for men in the general population.

STUDY DESIGN, SIZE, DURATION

This prospective cohort study comprised 501 male partners in couples discontinuing contraception to become pregnant, who were recruited from 16 US counties using population-based sampling frameworks from 2005 to 2009.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Urine and semen samples were obtained at baseline from 473 (94%) men, of whom 378 (80%) men provided a second sample the following month. Urine was analyzed for 14 monoester metabolites of phthalate diesters by high-performance liquid chromatography coupled to tandem mass spectrometry. Semen samples were analyzed for 34 quality parameters categorized as general, motility, morphology, sperm head and sperm chromatin structure.

MAIN RESULTS AND THE ROLE OF CHANCE

Urinary mono-[2-(carboxymethyl) hexyl] phthalate (MCMHP), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-benzyl phthalate (MBzP), and mono-isononyl phthalate (MNP) were significantly associated with lower total sperm counts and concentrations, larger sperm head sizes, higher proportions of megalo head sperm morphology, and/or other morphological changes. Urinary mono-methyl phthalate (MMP) and mono-cyclohexyl phthalate (MCPP) were significantly associated with lower sperm motility, and urine mono-2-ethylhexyl phthalate (MEHP) was significantly associated with higher sperm motility.

LIMITATIONS, REASONS FOR CAUTION

While adverse associations were observed, the implications of the findings for couple fecundity and fertility remain to be established. Cautious interpretation is needed in light of reliance on a single measurement of phthalate measure and no correction for multiple comparisons.

Erratum: Single-molecule force measurement via optical tweezers reveals different kinetic features of two BRaf mutants responsible for cardio-facial-cutaneous (CFC) syndrome: errata

We correct the omission of the construct and protein purification method in our recent paper [Biomed. Opt. Express 4(12), 2835-2845 (2013)].[This corrects the article on p. 2835 in vol. 4, PMID: 24409384.].

Single-molecule force measurement via optical tweezers reveals different kinetic features of two BRaf mutants responsible for cardio-facial-cutaneous (CFC) syndrome

BRaf (B- Rapid Accelerated Fibrosarcoma) protein is an important serine/threonine-protein kinase. Two domains on BRaf can independently bind its upstream kinase, Ras (Rat Sarcoma) protein. These are the Ras binding domain (RBD) and cysteine-rich-domain (CRD). Herein we use customized optical tweezers to compare the Ras binding process in two pathological mutants of BRaf responsible for CFC syndrome, abbreviated BRaf (A246P) and BRaf (Q257R). The two mutants differ in their kinetics of Ras-binding, though both bind Ras with similar increased overall affinity. BRaf (A246P) exhibits a slightly higher Ras/CRD unbinding force and a significantly higher Ras/RBD unbinding force versus the wild type. The contrary phenomenon is observed in the Q257R mutation. Simulations of the unstressed-off rate, koff (0), yield results in accordance with the changes revealed by the mean unbinding force. Our approach can be applied to rapidly assess other mutated proteins to deduce the effects of mutation on their kinetics compared to wild type proteins and to each other.

The influence of sporadic anovulation on hormone levels in ovulatory cycles

STUDY QUESTION

Do ovulatory hormone profiles among healthy premenopausal women differ between women with and without sporadic anovulation?

SUMMARY ANSWER

Women with one anovulatory cycle tended to have lower estradiol, progesterone and LH peak levels during their ovulatory cycle.

WHAT IS KNOWN ALREADY

Anovulation occurs sporadically in healthy premenopausal women, but the influence of hormones in a preceding cycle and the impact on a subsequent cycle's hormone levels is unknown.

STUDY DESIGN, SIZE, DURATION

The BioCycle Study was a prospective cohort including 250 healthy regularly menstruating women, 18-44 years of age, from Western New York with no history of menstrual or ovulation disorders. The women were followed with up to eight study visits per cycle for two cycles, most of which were consecutive.

PARTICIPANTS/MATERIALS, SETTING AND METHODS

All study visits were timed to menstrual cycle phase using fertility monitors and located at the University at Buffalo women's health research center from 2005 to 2007. The main outcomes measured were estradiol, progesterone, LH and follicle-stimulating hormone levels in serum at up to 16 visits over two cycles. Anovulation was defined as peak serum progesterone concentrations ≤5 ng/ml and no serum LH peak detected during the mid- or late-luteal phase visit.

MAIN RESULTS AND THE ROLE OF CHANCE

Reproductive hormone concentrations were lower during anovulatory cycles, but significant reductions were also observed in estradiol (-25%, P = 0.003) and progesterone (-22%, P = 0.001) during the ovulatory cycles of women with one anovulatory cycle compared with women with two ovulatory cycles. LH peak concentrations were decreased in the ovulatory cycle of women with an anovulatory cycle (significant amplitude effect, P = 0.004; geometric mean levels 38% lower, P < 0.05).

LIMITATIONS, REASONS FOR CAUTION

Follow-up was limited to two menstrual cycles, and no ultrasound assessment of ovulation was available. Data were missing for a total of 168 of a possible 4072 cycle visits (4.1%), though all women had at least five visits per cycle (94% had seven or more per cycle).

WIDER IMPLICATIONS OF THE FINDINGS

These results suggest a possible underlying cause of anovulation, such as a longer-term subclinical follicular, ovarian or hypothalamic/pituitary dysfunction, even among healthy, regularly menstruating women.

Correlated biomarker measurement error: an important threat to inference in environmental epidemiology

Utilizing multiple biomarkers is increasingly common in epidemiology. However, the combined impact of correlated exposure measurement error, unmeasured confounding, interaction, and limits of detection (LODs) on inference for multiple biomarkers is unknown. We conducted data-driven simulations evaluating bias from correlated measurement error with varying reliability coefficients (R), odds ratios (ORs), levels of correlation between exposures and error, LODs, and interactions. Blood cadmium and lead levels in relation to anovulation served as the motivating example, based on findings from the BioCycle Study (2005-2007). For most scenarios, main-effect estimates for cadmium and lead with increasing levels of positively correlated measurement error created increasing downward or upward bias for OR > 1.00 and OR < 1.00, respectively, that was also a function of effect size. Some scenarios showed bias for cadmium away from the null. Results subject to LODs were similar. Bias for main and interaction effects ranged from -130% to 36% and from -144% to 84%, respectively. A closed-form continuous outcome case solution provides a useful tool for estimating the bias in logistic regression. Investigators should consider how measurement error and LODs may bias findings when examining biomarkers measured in the same medium, prepared with the same process, or analyzed using the same method.

Interactions between whey proteins and salivary proteins as related to astringency of whey protein beverages at low pH

Whey protein beverages have been shown to be astringent at low pH. In the present study, the interactions between model whey proteins (β-lactoglobulin and lactoferrin) and human saliva in the pH range from 7 to 2 were investigated using particle size, turbidity, and ζ-potential measurements and sodium dodecyl sulfate-PAGE. The correlation between the sensory results of astringency and the physicochemical data was discussed. Strong interactions between β-lactoglobulin and salivary proteins led to an increase in the particle size and turbidity of mixtures of both unheated and heated β-lactoglobulin and human saliva at pH ∼3.4. However, the large particle size and high turbidity that occurred at pH 2.0 were the result of aggregation of human salivary proteins. The intense astringency in whey protein beverages may result from these increases in particle size and turbidity at these pH values and from the aggregation and precipitation of human salivary proteins alone at pH <3.0. The involvement of salivary proteins in the interaction is a key factor in the perception of astringency in whey protein beverages. At any pH, the increases in particle size and turbidity were much smaller in mixtures of lactoferrin and saliva, which suggests that aggregation and precipitation may not be the only mechanism linked to the perception of astringency in whey protein.

High-Pressure–Induced Interactions Between Milk Fat Globule Membrane Proteins and Skim Milk Proteins in Whole Milk

The association of beta-lactoglobulin (beta-LG) and alpha-lactalbumin (alpha-LA) with milk fat globule membrane (MFGM), when whole milk was treated by high pressure in the range 100 to 800 MPa, was investigated using sodium dodecyl sulfate (SDS)-PAGE under reducing and nonreducing conditions. In SDS-PAGE under reducing conditions, beta-LG was observed in the MFGM material isolated from milk treated at 100 to 800 MPa for 30 min, and small amounts of alpha-LA and kappa-casein were also observed at pressures >600 MPa for 30 min. However, these proteins were not observed in SDS-PAGE under nonreducing conditions. These results indicate that beta-LG and alpha-LA associated with MFGM proteins via disulfide bonds during the high-pressure treatment of whole milk. The amount of beta-LG associated with the MFGM increased with an increase in pressure up to 800 MPa and with increasing time of pressure treatment. The maximum value for beta-LG association with the MFGM was approximately 0.75 mg/g of fat. Of the major original MFGM proteins, no change in butyrophilin was observed during the high-pressure treatment of whole milk, whereas xanthine oxidase was reduced to some extent beyond 400 MPa. In contrast to the behavior during heat treatment, PAS 6 and PAS 7 were stable during high-pressure treatment, and they remained associated with the MFGM.

Optical properties of singly charged conjugated oligomers: A coupled-cluster equation of motion study

We have implemented a coupled-cluster equation of motion approach combined with the intermediate neglect of differential overlap parametrization and applied it to study the excited states and optical absorptions in positively and negatively charged conjugated oligomers. The method is found to be both reliable and efficient. The theoretical results are in very good agreement with experiments and confirm that there appear two subgap absorption peaks upon polaron formation. Interestingly, the relative intensities of the polaron-induced subgap absorptions can be related to the extent of the lattice geometry relaxations.

An analysis of two polymorphic points of the 7th intron of human p53 gene

OBJECTIVE

To detect polymorphic points of the 7th intron of human p53 oncogene.

METHODS

Polymerase chain reaction (PCR) and double- strand DNA direct sequencing were used to analyse sequence alteration of p53 intron 7. One hundred and five cases of normal human peripheral blood samples with no genetic relation were investigated.

RESULTS

There were two polymorphic points in the 7th intron of p53 gene. The first one was localized at 73 base pair (bp) to 3'-end of exon 7; the other one at 93. Three genotypes were found. Twenty-two cases were of type TG, 37 cases were of type CT, and the other 46 cases were of heterozygote. Because the first point was alteration of GGGCCC to GGGTCC or its heterozygote, it had a point alteration of enzyme Apa I.

CONCLUSION

There are two polymorphic points in the 7th intron of human p53 gene, which may be of importance to identification of individual genetic relation and to judging of a case in forensic medicine.

Detection filters and algorithm fusion for ATR

Detection involves locating all candidate regions of interest (objects) in a scene independent of the object class with object distortions and contrast differences, etc., present. It is one of the most formidable problems in automatic target recognition, since it involves analysis of every local scene region. We consider new detection algorithms and the fusion of their outputs to reduce the probability of false alarm P(FA) while maintaining high probability of detection P(D). Emphasis is given to detecting obscured targets in infrared imagery.

Morphological and wavelet transforms for object detection and image processing

We consider the problem of detecting multiple distorted objects in an input scene with clutter. The input scenes contain different types of background clutter and multiple objects in different classes, with different object aspect views, different object representations, hot/cold/bimodal/partial object variations, and high/low contrast object variations. Several new optical morphological operations for use in the above detection problem and in other general low-level image-processing applications are described, and several examples of their use are provided. For difficult detection problems in which high detection rates and low false-alarm rates are required we combine morphological operations and optical wavelet transforms to reduce clutter and improve object detection. The details of this set of filters and initial testresults are given. The most computationally demanding operations required in all cases are realizable on an optical correlator.