Perspiration-based wearable biosensors facilitate continuous monitoring of individuals' health states with real-time and molecular-level insight. The inherent inaccessibility of sweat in sedentary individuals in large volume (≥10 μL) for on-demand and in situ analysis has limited our ability to capitalize on this noninvasive and rich source of information. A wearable and miniaturized iontophoresis interface is an excellent solution to overcome this barrier. The iontophoresis process involves delivery of stimulating agonists to the sweat glands with the aid of an electrical current. The challenge remains in devising an iontophoresis interface that can extract sufficient amount of sweat for robust sensing, without electrode corrosion and burning/causing discomfort in subjects. Here, we overcame this challenge through realizing an electrochemically enhanced iontophoresis interface, integrated in a wearable sweat analysis platform. This interface can be programmed to induce sweat with various secretion profiles for real-time analysis, a capability which can be exploited to advance our knowledge of the sweat gland physiology and the secretion process. To demonstrate the clinical value of our platform, human subject studies were performed in the context of the cystic fibrosis diagnosis and preliminary investigation of the blood/sweat glucose correlation. With our platform, we detected the elevated sweat electrolyte content of cystic fibrosis patients compared with that of healthy control subjects. Furthermore, our results indicate that oral glucose consumption in the fasting state is followed by increased glucose levels in both sweat and blood. Our solution opens the possibility for a broad range of noninvasive diagnostic and general population health monitoring applications.W earable biosensors have received considerable attention owing to their great promise for a wide range of clinical and physiological applications (1-10). Despite significant progress made in printed and flexible biosensors in the field, a majority of wearable devices focus on monitoring of physical activity or selected electrophysiological parameters, providing only limited information regarding physiological changes of complex homeostatic responses (4-10). Wearable chemical sensors offer great opportunities for collecting physiological information at the molecular level (3,(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19). Recently research advances have resulted in a variety of wearable sweat sensors that can be used for real-time analysis of sweat biomarkers including electrolytes, metabolites, and heavy metals (11)(12)(13)(14)(15)(16)(17)(18)(19)(20). We recently demonstrated a fully integrated wearable sensing system for real-time monitoring of multiple analytes in human perspiration during physical exercise which allows accurate measurement of sweat analytes through signal processing and calibration (16).The inherent inaccessibility of sweat in sedentary individuals in large volume (≥10 μL) for on-demand and in situ analysis remains to limit our ...

Nearly finished sequences for model organisms provide a foundation from which to explore genomic diversity among other taxonomic groups. We explore genome-wide microsynteny patterns between the rice sequence and two sorghum physical maps that integrate genetic markers, bacterial artificial chromosome (BAC) fingerprints, and BAC hybridization data. The sorghum maps largely tile a genomic component containing 41% of BACs but 80% of single-copy genes that shows conserved microsynteny with rice and partially tile a nonsyntenic component containing 46% of BACs but only 13% of single-copy genes. The remaining BACs are centromeric (4%) or unassigned (8%). The two genomic components correspond to cytologically discernible ''euchromatin'' and ''heterochromatin.'' Gene and repetitive DNA distributions support this classification. Greater microcolinearity in recombinogenic (euchromatic) than nonrecombinogenic (heterochromatic) regions is consistent with the hypothesis that genomic rearrangements are usually deleterious, thus more likely to persist in nonrecombinogenic regions by virtue of Muller's ratchet. Interchromosomal centromeric rearrangements may have fostered diploidization of a polyploid cereal progenitor. Model plant sequences better guide studies of related genomes in recombinogenic than nonrecombinogenic regions. Bridging of 35 physical gaps in the rice sequence by sorghum BAC contigs illustrates reciprocal benefits of comparative approaches that extend at least across the cereals and perhaps beyond.comparative genomics ͉ Oryza ͉ synteny T he grasses (Poaceae) provide most of mankind's caloric intake and a growing share of our fuel. The best-studied grasses, leading cereal crops, shared a common paleopolyploid ancestor Ϸ42-47 million years ago (mya) (1). Cereals show much colinearity of genetic maps and often have important traits controlled by quantitative trait loci at corresponding locations (2). Despite these similarities, the cereals have diverged remarkably in genome size from Ϸ430 million base pairs (MBP) in rice (3) to 15,966 MBP in wheat (3), largely due to differential repetitive DNA amplification and elimination.As a model for tropical grasses, sorghum [Sorghum bicolor (SB)] is a logical complement to rice (Oryza), in that it has biochemical and morphological specializations to improve carbon assimilation at high temperatures (C4 photosynthesis). By contrast, rice uses C3 photosynthesis more typical of temperate grasses. The Ϸ760-MBP (3) sorghum genome is a logical bridge to the Ϸ2,500-MBP (3) maize genome, and the Ϸ4,000-MBP (3) genome of sugarcane, the world's leading biomass͞biofuels crop. Sorghum shared common ancestry with maize (12 mya) and sugarcane (5 mya), much more recently than rice (42-47 mya). The most recent whole-genome duplication in sorghum appears to be Ϸ70 mya (1) vs. Ϸ12 mya in maize (4) and Ͻ5 mya in sugarcane (5), promising a higher success rate in relating sorghum genes to phenotypes by knockouts than either maize or sugarcane genes. Comparison of SB and closely related Sorghum...

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Aims Use of molecular sequencing methods in periprosthetic joint infection (PJI) diagnosis and organism identification have gained popularity. Next-generation sequencing (NGS) is a potentially powerful tool that is now commercially available. The purpose of this study was to compare the diagnostic accuracy of NGS, polymerase chain reaction (PCR), conventional culture, the Musculoskeletal Infection Society (MSIS) criteria, and the recently proposed criteria by Parvizi et al in the diagnosis of PJI. Methods In this retrospective study, aspirates or tissue samples were collected in 30 revision and 86 primary arthroplasties for routine diagnostic investigation for PJI and sent to the laboratory for NGS and PCR. Concordance along with statistical differences between diagnostic studies were calculated. Results Using the MSIS criteria to diagnose PJI as the reference standard, the sensitivity and specificity of NGS were 60.9% and 89.9%, respectively, while culture resulted in sensitivity of 76.9% and specificity of 95.3%. PCR had a low sensitivity of 18.4%. There was no significant difference based on sample collection method (tissue swab or synovial fluid) (p = 0.760). There were 11 samples that were culture-positive and NGS-negative, of which eight met MSIS criteria for diagnosing infection. Conclusion In our series, NGS did not provide superior sensitivity or specificity results compared to culture. PCR has little utility as a standalone test for PJI diagnosis with a sensitivity of only 18.4%. Currently, several laboratory tests for PJI diagnosis should be obtained along with the overall clinical picture to help guide decision-making for PJI treatment. Cite this article: Bone Joint J 2021;103-B(1):26–31.

Aims Antifibrinolytic agents, including tranexamic acid (TXA) and epsilon-aminocaproic acid (EACA), have been shown to be safe and effective for decreasing perioperative blood loss and transfusion following total hip arthroplasty (THA) and total knee arthroplasty (TKA). However, there are few prospective studies that directly compare these agents. The purpose of this study was to compare the benefits of intraoperative intravenous TXA with EACA. Patients and Methods A total of 235 patients (90 THA and 145 TKA) were enrolled in this prospective, randomized controlled trial at a single tertiary-care referral centre. In the THA cohort, 53.3% of the patients were female with a median age of 59.8 years (interquartile range (IQR) 53.3 to 68.1). In the TKA cohort, 63.4% of the patients were female with a median age of 65.1 years (IQR 59.4 to 69.5). Patients received either TXA (n = 119) or EACA (n = 116) in two doses intraoperatively. The primary outcome measures included change in haemoglobin level and blood volume, postoperative drainage, and rate of transfusion. Secondary outcome measures included postoperative complications, cost, and length of stay (LOS). Results TKA patients who received EACA had greater drainage (median 320 ml (IQR 185 to 420) vs 158 ml (IQR 110 to 238); p < 0.001), increased loss of blood volume (891 ml (IQR 612 to 1203) vs 661 ml (IQR 514 to 980); p = 0.014), and increased haemoglobin change from the preoperative level (2.1 ml (IQR 1.7 to 2.8) vs 1.9 ml (IQR 1.2 to 2.4); p = 0.016) compared with patients who received TXA. For the THA cohort, no statistically significant differences were observed in any haematological outcome measure. One patient in the EACA group required transfusion. No patient in the TXA group required transfusion. There were no statistically significant differences in number or type of postoperative complications or LOS for either THA or TKA patients regardless of whether they received TXA or EACA. Conclusion For hip and knee arthroplasty procedures, EACA is associated with increased perioperative blood loss compared with TXA. However, there is no significant difference in transfusion rate. While further prospective studies are needed to compare the efficacy of each agent, we currently recommend orthopaedic surgeons to select their antifibrinolytic based on cost and regional availability. Cite this article: Bone Joint J 2019;101-B:1093–1099.