Corrigendum: Associations between omega-3 fatty acids and insulin resistance and body composition in women with polycystic ovary syndrome.

[This corrects the article DOI: 10.3389/fnut.2022.1016943.].

Unveiling the Morphological and Physical Mechanism of Burn-in Loss Alleviation by Ternary Matrix Toward Stable and Efficient All-Polymer Solar Cells.

All-polymer solar cells (All-PSCs) are considered the most promising candidate in achieving both efficient and stable organic photovoltaic devices, yet the field has rarely presented an in-depth understanding of corresponding device stability while efficiency is continuously boosted via the innovation of polymer acceptors. Herein, a ternary matrix is built for all-PSCs with optimized morphology, improved film ductility and importantly, boosted efficiency and better operational stability than its parental binary counterparts, as a platform to study the underlying mechanism. The target system PQM-Cl:PTQ10:PY-IT (0.8:0.2:1.2) exhibits an alleviated burn-in loss of morphology and efficiency under light soaking, which supports its promoted device lifetime. The comprehensive characterizations of fresh and light-soaked active layers lead to a clear illustration of opposite morphological and physical degradation direction of PQM-Cl and PTQ10, thus resulting in a delicate balance at the optimal ternary system. Specifically, the enlarging tendency of PQM-Cl and shrinking preference of PTQ10 in terms of phase separation leads to a stable morphology in their mixing phase; the hole transfer kinetics of PQM-Cl:PY-IT host is stabilized by incorporating PTQ10. This work succeeds in reaching a deep insight into all-PSC's stability promotion by a rational ternary design, which booms the prospect of gaining high-performance all-PSCs.

CircMED12L Protects Against Hydrogen Peroxide-induced Apoptotic and Oxidative Injury in Human Lens Epithelial Cells by miR-34a-5p/ALCAM axis.

PURPOSE: Cataract is the leading cause of visual impairment and reversible blindness. Despite advances in surgical removal of cataracts, cataract continues to be a leading public-health issue due to the complications after surgery. Circular RNAs (circRNAs) have been showed to be implicated in the pathophysiology of age-related cataract (ARC). Herein, this work elucidated the role and mechanism of circMED12L in the process of ARC. METHODS: Human lens epithelial cells (HLECs) were exposed to hydrogen peroxide (H2O2) in experimental groups. Levels of genes and proteins were measured by qRT-PCR and western blotting. Cell growth was evaluated by Cell Counting Kit-8 (CCK-8) assay and flow cytometry, respectively. The oxidative stress was assessed by detecting the activity of malondialdehyde, catalase, and superoxide dismutase. The interaction between miR-34a-5p and circMED12L or ALCAM (activated leukocyte cell adhesion molecule) was validated using dual-luciferase reporter and RNA immunoprecipitation assays. RESULTS: CircMED12L expression was lower in the lens epithelium of ARC patients and H2O2-induced HLECs compared with the normal individuals and untreated cells. Functionally, forced expression of circMED12L could alleviate H2O2-induced viability inhibition, as well as apoptotic and oxidative injury in HLECs. Mechanistically, circMED12L/miR-34a-5p/ALCAM constituted a feedback loop in HLECs. MiR-34a-5p was increased, while ALCAM was decreased in ARC patients and H2O2-induced HLECs. High expression of miR-34a-5p reversed the protective effects of circMED12L on HLECs under H2O2 treatment. Besides, inhibition of miR-34a-5p could repress H2O2-induced apoptotic and oxidative injury in HLECs, which were abolished by subsequent ALCAM knockdown. CONCLUSION: Overexpression of circMED12L could protect against H2O2-induced apoptosis and oxidative stress in HLECs by miR-34a-5p/ALCAM axis.

Associations between omega-3 fatty acids and insulin resistance and body composition in women with polycystic ovary syndrome.

Background: Polycystic ovary syndrome (PCOS) is strongly associated with abdominal obesity and insulin resistance and effective approaches to nutrition (e.g., omega-3 fatty acids intake) might improve the cardiometabolic risk profile. This study aimed to examine the associations of dietary and serum omega-3 fatty acids with insulin resistance (IR) and body composition among PCOS patients. Methods: A total of 185 patients with PCOS were included in our analysis. Dietary information was collected through face-to-face interviews using a 102-item food frequency questionnaire (FFQ). Serum omega-3 fatty acid levels were measured with the gas chromatography method. Body composition was measured by both dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance (BIA) methods. The multivariable linear regression model was applied to analyze the associations of dietary and serum omega-3 fatty acids with the levels of Homeostasis Model Assessment for Insulin Resistance (HOMA-IR) and body composition parameters among PCOS patients. Results: Our results indicated that the dietary long-chain omega-3 polyunsaturated fatty acids (PUFA) intakes were negatively associated with HOMA-IR (ß = -0.089, P = 0.040), fat mass (ß = -0.022, P = 0.047), and body fat percentage (ß = -0.026, P = 0.032). For serum biomarkers, higher total omega-3 PUFAs levels (ß = -0.158, P = 0.021) and long-chain omega-3 PUFAs levels (ß = -0.187, P < 0.001), particularly eicosapentaenoic acid (EPA) (ß = -164, P = 0.011) and docosahexaenoic acid (DHA) (ß = -0.158, P = 0.001) were also associated with decreased HOMA-IR. In addition, generally, dietary and serum long-chain omega-3 PUFA levels, DPA, and DHA levels were both positively associated with muscle mass measured by DXA; whereas serum total, long-chain and individual omega-3 PUFA levels (e.g., DPA, EPA, and DHA) were all negatively associated with fat mass and body fat percentage. These findings were further confirmed by the findings for body composition measured by the BIA method. Conclusion: Higher levels of dietary and serum omega-3 PUFAs, particularly long-chain omega PUFAs (DPA and DHA), might have beneficial effects on metabolic parameters and body composition among PCOS patients.

End-to-End Fusion of Hyperspectral and Chlorophyll Fluorescence Imaging to Identify Rice Stresses.

Herbicides and heavy metals are hazardous substances of environmental pollution, resulting in plant stress and harming humans and animals. Identification of stress types can help trace stress sources, manage plant growth, and improve stress-resistant breeding. In this research, hyperspectral imaging (HSI) and chlorophyll fluorescence imaging (Chl-FI) were adopted to identify the rice plants under two types of herbicide stresses (butachlor (DCA) and quinclorac (ELK)) and two types of heavy metal stresses (cadmium (Cd) and copper (Cu)). Visible/near-infrared spectra of leaves (L-VIS/NIR) and stems (S-VIS/NIR) extracted from HSI and chlorophyll fluorescence kinetic curves of leaves (L-Chl-FKC) and stems (S-Chl-FKC) extracted from Chl-FI were fused to establish the models to detect the stress of the hazardous substances. Novel end-to-end deep fusion models were proposed for low-level, middle-level, and high-level information fusion to improve identification accuracy. Results showed that the high-level fusion-based convolutional neural network (CNN) models reached the highest detection accuracy (97.7%), outperforming the models using a single data source (<94.7%). Furthermore, the proposed end-to-end deep fusion models required a much simpler training procedure than the conventional two-stage deep learning fusion. This research provided an efficient alternative for plant stress phenotyping, including identifying plant stresses caused by hazardous substances of environmental pollution.

Dietary Acid Load Was Positively Associated with the Risk of Hip Fracture in Elderly Adults.

Previous studies have shown that dietary acid load (DAL) harms bone health, but the evidence is inconsistent and insufficient. This study examined the relationships between DAL and the risk of hip fracture. This case−control study contained 1070 pairs of 1:1 age-, city-, and gender-matched incident cases and controls (mean age, 71 years) recruited in Guangdong, China. Dietary information was collected using a validated 79-item food frequency questionnaire through face-to-face interviews. DAL was estimated based on established algorithms for the potential renal acid load (PRAL) and net endogenous acid production (NEAP). Higher PRAL and NEAP were dose-dependently associated with a higher risk of hip fracture in both the conditional logistic regression model and restricted cubic spline analysis after adjusting for potential covariates. The multivariate-adjusted odds ratios and 95% CI of hip fracture for tertiles 2 and 3 (vs. 1) of DAL were 1.63 (1.18, 2.25) and 1.92 (1.36, 2.71) for PRAL and 1.81 (1.30, 2.53) and 2.55 (1.76, 3.71) for NEAP in all participants (all p-trends < 0.001), respectively. Subgroup analyses showed more pronounced associations in participants with a lower body mass index. Our findings suggested positive associations between the estimated DAL and the risk of hip fractures in the elderly Chinese population.

Nonhalogenated Dual-Slot-Die Processing Enables High-Efficiency Organic Solar Cells.

Organic solar cells (OSCs) are promising candidates for next-generation photovoltaic technologies, with their power conversion efficiencies (PCEs) reaching 19%. However, the typically used spin-coating method, toxic halogenated processing solvents, and the conventional bulk-heterojunction (BHJ), which causes excessive charge recombination, hamper the commercialization and further efficiency promotion of OSCs. Here, a simple but effective dual-slot-die sequential processing (DSDS) strategy is proposed to address the above issues by achieving a continuous solution supply, avoiding the solubility limit of the nonhalogen solvents, and creating a graded-BHJ morphology. As a result, an excellent PCE of 17.07% is obtained with the device processed with o-xylene in an open-air environment with no post-treatment required, while a PCE of over 14% is preserved in a wide range of active-layer thickness. The unique film-formation mechanism is further identified during the DSDS processing, which suggests the formation of the graded-BHJ morphology by the mutual diffusion between the donor and acceptor and the subsequent progressive aggregation. The graded-BHJ structure leads to improved charge transport, inhibited charge recombination, and thus an excellent PCE. Therefore, the newly developed DSDS approach can effectively contribute to the realm of high-efficiency and eco-friendly OSCs, which can also possibly be generalized to other organic photoelectric devices.

Versatile Sequential Casting Processing for Highly Efficient and Stable Binary Organic Photovoltaics.

Forming an ideal bulk heterojunction (BHJ) morphology is a critical issue governing the photon to electron process in organic solar cells (OSCs). Complementary to the widely-used blend casting (BC) method for BHJ construction, sequential casting (SC) can also enable similar or even better morphology and device performance for OSCs. Here, BC and SC methods on three representative donor:acceptor (D:A) blends are utilized, that is, PM6:PC71 BM, PM6:IT-4F and PM6:L8-BO. Higher power conversion efficiencies (PCEs) in all cases by taking advantage of beneficial morphology from SC processing are achieved, and a champion PCE of 18.86% (certified as 18.44%) based on the PM6:L8-BO blend is reached, representing the record value among binary OSCs. The observations on phase separation and vertical distribution inspire the proposal of the swelling-intercalation phase-separation model to interpret the morphology evolution during SC processing. Further, the vertical phase segregation is found to deliver an improvement of device performance via affecting the charge transport and collection processes, as evidenced by the D:A-ratio-dependent photovoltaic properties. Besides, OSCs based on SC processing show advantages on device photostability and upscale fabrication. This work demonstrates the versatility and efficacy of the SC method for BHJ-based OSCs.

Dietary and serum n-3 PUFA and polycystic ovary syndrome: a matched case-control study.

The results of epidemiological studies involving n-3 PUFA and polycystic ovary syndrome (PCOS) are scarce. This matched case-control study assessed the associations between n-3 PUFA and PCOS prevalence in 325 pairs of PCOS cases and healthy controls. Dietary information was assessed using a 102-item FFQ. Fatty acids in serum phospholipids were measured with a GC method. We found that n-3 PUFA in serum phospholipids were inversely associated with PCOS prevalence, including total, long-chain and individual PUFA (e.g. docosapentaenoic acid (DPA), EPA and DHA). Compared with the lowest tertile (T1), the adjusted OR and their 95% CI for the highest tertile (T3) were 0·63 (0·40, 0·93) for total n-3 PUFA, 0·60 (0·38, 0·92) for long-chain n-3 PUFA, 0·68 (0·45, 1·01) for DHA, 0·70 (0·45, 1·05) for EPA and 0·72 (0·45, 1·08) for DPA. For dietary intake of n-3 PUFA, significant inverse associations were found only for long-chain n-3 PUFA (Ptrend = 0·001), EPA (Ptrend = 0·047) and DHA (Ptrend = 0·030). Both dietary and serum n-3 PUFA, mainly EPA and DPA, were negatively correlated with PCOS-related parameters, such as BMI, fasting insulin, total testosterone and high-sensitivity C-reactive protein, but positively correlated with follicle-stimulating hormone and sex hormone-binding globulin. These results indicated inverse associations between n-3 PUFA, especially long-chain n-3 PUFA, and PCOS prevalence. Higher intakes of n-3 PUFA might be considered a protective factor for PCOS among Chinese females.

Two-Dimensional Polycyclic Photovoltaic Molecule with Low Trap Density for High-Performance Photocatalytic Hydrogen Evolution.

Typical organic semiconductors show a high trap density of states (1016 -1018  cm-3 ), providing a large number of centers for charge-carrier recombination, thus hindering the development of photocatalytic hydrogen evolution. Here, we design and synthesize a two-dimensional polycyclic photovoltaic material, named as TPP, to reduce the trap density to as low as 2.3×1015  cm-3 , which is 1-3 orders of magnitude lower than those of typical organic semiconductors. Moreover, TPP exhibits a broad and strong absorption, ordered molecular packing with a large crystalline coherence length and enhanced electron mobility. Then, the bulk heterojunction nanoparticles (BHJ-NPs) based on a blend of polymer donor (PM6) and TPP exhibit an average hydrogen evolution rate (HER) of 64.31 mmol h-1 g-1 under AM1.5G sunlight (100 mW cm-2 ), and 72.75 mmol h-1 g-1 under 330-1100 nm illumination (198 mW cm-2 ) higher than that of the control NPs based on typical PM6 : Y6 (62.67 mmol h-1 g-1 ).

Hyperspectral Imaging Combined With Deep Transfer Learning for Rice Disease Detection.

Various rice diseases threaten the growth of rice. It is of great importance to achieve the rapid and accurate detection of rice diseases for precise disease prevention and control. Hyperspectral imaging (HSI) was performed to detect rice leaf diseases in four different varieties of rice. Considering that it costs much time and energy to develop a classifier for each variety of rice, deep transfer learning was firstly introduced to rice disease detection across different rice varieties. Three deep transfer learning methods were adapted for 12 transfer tasks, namely, fine-tuning, deep CORrelation ALignment (CORAL), and deep domain confusion (DDC). A self-designed convolutional neural network (CNN) was set as the basic network of the deep transfer learning methods. Fine-tuning achieved the best transferable performance with an accuracy of over 88% for the test set of the target domain in the majority of transfer tasks. Deep CORAL obtained an accuracy of over 80% in four of all the transfer tasks, which was superior to that of DDC. A multi-task transfer strategy has been explored with good results, indicating the potential of both pair-wise, and multi-task transfers. A saliency map was used for the visualization of the key wavelength range captured by CNN with and without transfer learning. The results indicated that the wavelength range with and without transfer learning was overlapped to some extent. Overall, the results suggested that deep transfer learning methods could perform rice disease detection across different rice varieties. Hyperspectral imaging, in combination with the deep transfer learning method, is a promising possibility for the efficient and cost-saving field detection of rice diseases among different rice varieties.

Application of Visible/Infrared Spectroscopy and Hyperspectral Imaging With Machine Learning Techniques for Identifying Food Varieties and Geographical Origins.

Food quality and safety are strongly related to human health. Food quality varies with variety and geographical origin, and food fraud is becoming a threat to domestic and global markets. Visible/infrared spectroscopy and hyperspectral imaging techniques, as rapid and non-destructive analytical methods, have been widely utilized to trace food varieties and geographical origins. In this review, we outline recent research progress on identifying food varieties and geographical origins using visible/infrared spectroscopy and hyperspectral imaging with the help of machine learning techniques. The applications of visible, near-infrared, and mid-infrared spectroscopy as well as hyperspectral imaging techniques on crop food, beverage, fruits, nuts, meat, oil, and some other kinds of food are reviewed. Furthermore, existing challenges and prospects are discussed. In general, the existing machine learning techniques contribute to satisfactory classification results. Follow-up researches of food varieties and geographical origins traceability and development of real-time detection equipment are still in demand.

Time From HIV Infection to Diagnosis in the U.S., 2014-2018.

INTRODUCTION: Understanding the role of sociologic, structural, and biomedical factors that influence the length of time from HIV infection to diagnosis and reducing the time from infection to diagnosis are critical for achieving the goals of the Ending the HIV Epidemic initiative. In a retrospective analysis, the length of time from HIV infection to diagnosis and its association with individual- and facility-level attributes are determined. METHODS: Data reported by December 2019 to the U.S. National HIV Surveillance System for people with HIV diagnosed during 2014-2018 were analyzed during December 2020. A CD4 depletion model was used to estimate the time from HIV infection to diagnosis. RESULTS: During 2018, the median time from HIV infection to diagnosis was shorter for those infections diagnosed using the rapid testing algorithm (30.3 months, 95% CI=25.5, 34.5) than those diagnosed using the recommended (41.0 months, 95% CI=39.5, 42.0), traditional (37.0 months, 95% CI=29.5, 43.5), or other (35.5 months, 95% CI=32.5, 38.0) diagnostic testing algorithms. From 2014 to 2018, the time from HIV infection to diagnosis remained stable overall for all testing methods except for the traditional diagnostic testing algorithm. In multivariate analyses, those more likely to have HIV diagnosed closer to the time of infection were younger, were White, had transmission risk factors of injection drug use or heterosexual contact (for female individuals) or male-to-male sexual contact and injection drug use, or had HIV diagnosed at a correctional or screening facility (p<0.01). CONCLUSIONS: Providing access to expanded testing, including rapid testing in nonclinical settings, is likely to result in a decrease in the length of time a person is unaware of their HIV infection and thus reduce onward transmission of HIV infection.

The relationship between quantitative epicardial adipose tissue based on CT and coronary artery disease: A protocol for systematic review and meta-analysis.

BACKGROUND: Epicardial adipose tissue (EAT) is a kind of visceral adipose tissue with close proximity to coronary artery and myocardium, which can secrete cell factor, and influence the physiological function and pathophysiological process of myocardium and coronary artery. Clinical imaging diagnosis showed that the volume and thickness of EAT exists a certain relevance with coronary artery disease, but it lacked evidence of evidence-based medicine. The research on the implementation of this program will systematically evaluate the relationship of computed tomography (CT) quantitative EAT and coronary artery disease. METHOD: The English databases (Embase, PubMed, the Cochrane Library, Web of Science) and Chinese database (CNKI, Wanfang, China biomedical database, VIP) of computer retrieval has collected the case control clinical study of relationship between EAT and coronary artery disease from the establishment of the database to October 2020, which was conducted extraction and quality evaluation by 2 researchers independently for data included in the study, and was conducted Meta-analysis for the included literature by adopting RevMan5.3 software. RESULT: The research evaluated the correlation between EAT and coronary artery disease through the EAT thickness, EAT volume, and other indexes. CONCLUSION: The research has provided reliable evidence-based evidence for the correlation between CT EAT quantification and coronary artery disease. ETHICS AND DISSEMINATION: We will not publish private information from individuals. This kind of systematic review does not involve harming the rights of participants. No ethical approval was required. The results can be published in peer-reviewed journals or at relevant conferences. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/DVQNE.

Investigation on Data Fusion of Multisource Spectral Data for Rice Leaf Diseases Identification Using Machine Learning Methods.

Rice diseases are major threats to rice yield and quality. Rapid and accurate detection of rice diseases is of great importance for precise disease prevention and treatment. Various spectroscopic techniques have been used to detect plant diseases. To rapidly and accurately detect three different rice diseases [leaf blight (Xanthomonas oryzae pv. Oryzae), rice blast (Pyricularia oryzae), and rice sheath blight (Rhizoctonia solani)], three spectroscopic techniques were applied, including visible/near-infrared hyperspectral imaging (HSI) spectra, mid-infrared spectroscopy (MIR), and laser-induced breakdown spectroscopy (LIBS). Three different levels of data fusion (raw data fusion, feature fusion, and decision fusion) fusing three different types of spectral features were adopted to categorize the diseases of rice. Principal component analysis (PCA) and autoencoder (AE) were used to extract features. Identification models based on each technique and different fusion levels were built using support vector machine (SVM), logistic regression (LR), and convolution neural network (CNN) models. Models based on HSI performed better than those based on MIR and LIBS, with the accuracy over 93% for the test set based on PCA features of HSI spectra. The performance of rice disease identification varied with different levels of fusion. The results showed that feature fusion and decision fusion could enhance identification performance. The overall results illustrated that the three techniques could be used to identify rice diseases, and data fusion strategies have great potential to be used for rice disease detection.

Estimating the probability of diagnosis within 1 year of HIV acquisition.

BACKGROUND: Early diagnosis of HIV is important for the prevention of ongoing transmission and development of HIV-related illness. The purpose of this study is to develop an outcome indicator to monitor the progress in early HIV diagnosis. METHODS: Persons diagnosed with HIV in New York City and their first CD4 test results were used to estimate the distribution of HIV diagnosis delay, based on a CD4 count depletion model. The distribution was then used to estimate the probability of diagnosis within 1 year of HIV acquisition, which is the number of cases diagnosed in a given calendar year for which diagnosis occurred within 1 year of acquisition divided by the number of incident cases in that calendar year. RESULTS: In 2012-2016, the estimated annual probability of diagnosis within 1 year of HIV acquisition in New York City was 43.0% [95% confidence interval (CI): 37.9-48.2%), 42.5% (95% CI: 36.8--48.3%), 42.8% (95% CI: 36.3--49.2%), 42.9% (95% CI: 35.4--50.3%), and 42.2% (95% CI: 33.1--51.2%), respectively. CONCLUSION: National and local health jurisdictions should consider using this new outcome indicator, the probability of diagnosis within 1 year of HIV acquisition, to monitor their progress in early HIV diagnosis.

A novel standardized test system to evaluate dynamic visual acuity post trifocal or monofocal intraocular lens implantation: a multicenter study.

OBJECTIVES: To compare the dynamic visual acuity (DVA) following implantation of trifocal with monofocal intraocular lenses (IOL) and using a novel test system. METHODS: The present research was a retrospective, multicenter clinical study. Two hundred and ten eyes of 149 patients that underwent cataract phacoemulsification and IOL implantation were enrolled. One hundred and ten eyes of patients received trifocal (AT LISA tri839MP, Carl Zeiss Meditec, Germany) and 100 eyes received monofocal (Tecnis ZCB00, Abbott, United States) lenses and were evaluated 3 months after implantation. Outcome measures included monocular uncorrected distance (UDVA), intermediate (UIVA) and near (UNVA) visual acuity and best corrected distance visual acuity (BCDVA; logMAR units); contrast sensitivity under photopic, mesopic, with glare conditions; and dynamic visual acuity using a self-developed system. RESULTS: There was no statistically significant difference in baseline characteristics between groups. Monocular UDVA, UIVA, and UNVA were significantly better (all p < 0.001) in the trifocal IOL group, but not BCDVA. The trifocal IOL group showed better contrast sensitivity under photopic, mesopic, with or without glare conditions (p < 0.05) and statistically significantly better dynamic vision at 15, 30, 60, and 90 degrees per second (dps) compared with the monofocal group (all p < 0.001). The strength of positive association only between UIVA and dynamic visual acuity increased as the velocity increased, but not UDVA or UNVA. CONCLUSIONS: Diffractive trifocal IOL provides better postoperative full range vision acuity, contrast sensitivity, and dynamic vision compared with monofocal IOLs. And intermediate visual acuity is increasingly associated with DVA as the velocity increasing.

Clinical analysis of emergency exploratory laparotomy in patients with intractable postpartum hemorrhage.

OBJECTIVE: This study was performed to explore the causes and clinical characteristics of emergency exploratory laparotomy in patients with intractable postpartum hemorrhage. METHODS: This retrospective study was performed from January 2004 to December 2017. Patients with intractable postpartum hemorrhage were grouped according to the initial pathogenesis as determined by exploratory laparotomy: uterine atony, placental factors, coagulation dysfunction, or uterine rupture. RESULTS: This study involved 72 patients who underwent emergency exploratory laparotomy, accounting for 0.04% of total deliveries. Uterine preservation surgery and hysterectomy were performed in 31 and 41 patients, respectively. Abnormal events upon returning to the ward were primarily vaginal hemorrhage and pelvic hematoma. The frequency of uterine artery ligation was lower in the hysterectomy group than uterine preservation group. The prothrombin activity level, fibrinogen level, and platelet count before surgery were lower in the hysterectomy group than uterine preservation group. The international normalized ratio and activated partial thromboplastin time were higher in the hysterectomy group than uterine preservation group. In total, 44 patients developed complications. CONCLUSION: Placental implantation is a primary cause of hysterectomy after emergency laparotomy. However, the possibility of postpartum hemorrhage caused by coagulation disorders should not be ignored.

Identification of Soybean Varieties Using Hyperspectral Imaging Coupled with Convolutional Neural Network.

Soybean variety is connected to stress resistance ability, as well as nutritional and commercial value. Near-infrared hyperspectral imaging was applied to classify three varieties of soybeans (Zhonghuang37, Zhonghuang41, and Zhonghuang55). Pixel-wise spectra were extracted and preprocessed, and average spectra were also obtained. Convolutional neural networks (CNN) using the average spectra and pixel-wise spectra of different numbers of soybeans were built. Pixel-wise CNN models obtained good performance predicting pixel-wise spectra and average spectra. With the increase of soybean numbers, performances were improved, with the classification accuracy of each variety over 90%. Traditionally, the number of samples used for modeling is large. It is time-consuming and requires labor to obtain hyperspectral data from large batches of samples. To explore the possibility of achieving decent identification results with few samples, a majority vote was also applied to the pixel-wise CNN models to identify a single soybean variety. Prediction maps were obtained to present the classification results intuitively. Models using pixel-wise spectra of 60 soybeans showed equivalent performance to those using the average spectra of 810 soybeans, illustrating the possibility of discriminating soybean varieties using few samples by acquiring pixel-wise spectra.

Differences among diagnostic testing algorithms in the time from HIV diagnosis to care.

BACKGROUND: The association between the type of diagnostic testing algorithm for HIV infection and the time from diagnosis to care has not been fully evaluated. Here we extend an earlier analysis of this association by controlling for patient and diagnosing facility characteristics. STUDY DESIGN: Descriptive analysis of HIV infection diagnoses during 2016 reported to the National HIV Surveillance System through December 2017. Algorithm type: traditional = initial HIV antibody immunoassay followed by a Western blot or immunofluorescence antibody test; recommended = initial HIV antigen/antibody immunoassay followed by HIV-1/2 type-differentiating antibody test; rapid = two CLIA-waived rapid tests on the same date. RESULTS: In multivariate analyses controlling for patient and diagnosing facility characteristics, persons whose infection was diagnosed using the rapid algorithm were more likely to be linked to care within 30 days than those whose infection was diagnosed using the other testing algorithms (p < 0.01). The median time to link to care during a 30-day follow-up was 9.0 days (95% CI 8.0-12.0) after the rapid algorithm, 17.0 days (95% CI 17.0-18.0) after the recommended algorithm, and 23.0 days (95% CI 22.0-25.0) after the traditional algorithm. CONCLUSIONS: The time from HIV diagnosis to care varied with the type of testing algorithm. The median time to care was shortest for the rapid algorithm, longest for the traditional algorithm, and intermediate for the recommended algorithm. These results demonstrate the importance of choosing an algorithm with a short time between initial specimen collection and report of the final result to the patient.