Life Cycle Replacement by Gene Introduction under an Allee Effect in Periodical Cicadas

Periodical cicadas (Magicicada spp.) in the USA are divided into three species groups (-decim, -cassini, -decula) of similar but distinct morphology and behavior. Each group contains at least one species with a 17-year life cycle and one with a 13-year cycle; each species is most closely related to one with the other cycle. One explanation for the apparent polyphyly of 13- and 17-year life cycles is that populations switch between the two cycles. Using a numerical model, we test the general feasibility of life cycle switching by the introduction of alleles for one cycle into populations of the other cycle. Our results suggest that fitness reductions at low population densities of mating individuals (the Allee effect) could play a role in life cycle switching. In our model, if the 13-year cycle is genetically dominant, a 17-year cycle population will switch to a 13-year cycle given the introduction of a few 13-year cycle alleles under a moderate Allee effect. We also show that under a weak Allee effect, different year-classes (“broods”) with 17-year life cycles can be generated. Remarkably, the outcomes of our models depend only on the dominance relationships of the cycle alleles, irrespective of any fitness advantages

The Japanese Clinical Practice Guidelines for Management of Sepsis and Septic Shock 2020 (J-SSCG 2020)

The Japanese Clinical Practice Guidelines for Management of Sepsis and Septic Shock 2020 (J-SSCG 2020), a Japanese-specific set of clinical practice guidelines for sepsis and septic shock created as revised from J-SSCG 2016 jointly by the Japanese Society of Intensive Care Medicine and the Japanese Association for Acute Medicine, was first released in September 2020 and published in February 2021. An English-language version of these guidelines was created based on the contents of the original Japanese-language version. The purpose of this guideline is to assist medical staff in making appropriate decisions to improve the prognosis of patients undergoing treatment for sepsis and septic shock. We aimed to provide high-quality guidelines that are easy to use and understand for specialists, general clinicians, and multidisciplinary medical professionals. J-SSCG 2016 took up new subjects that were not present in SSCG 2016 (e.g., ICU-acquired weakness [ICU-AW], post-intensive care syndrome [PICS], and body temperature management). The J-SSCG 2020 covered a total of 22 areas with four additional new areas (patient- and family-centered care, sepsis treatment system, neuro-intensive treatment, and stress ulcers). A total of 118 important clinical issues (clinical questions, CQs) were extracted regardless of the presence or absence of evidence. These CQs also include those that have been given particular focus within Japan. This is a large-scale guideline covering multiple fields; thus, in addition to the 25 committee members, we had the participation and support of a total of 226 members who are professionals (physicians, nurses, physiotherapists, clinical engineers, and pharmacists) and medical workers with a history of sepsis or critical illness. The GRADE method was adopted for making recommendations, and the modified Delphi method was used to determine recommendations by voting from all committee members.As a result, 79 GRADE-based recommendations, 5 Good Practice Statements (GPS), 18 expert consensuses, 27 answers to background questions (BQs), and summaries of definitions and diagnosis of sepsis were created as responses to 118 CQs. We also incorporated visual information for each CQ according to the time course of treatment, and we will also distribute this as an app. The J-SSCG 2020 is expected to be widely used as a useful bedside guideline in the field of sepsis treatment both in Japan and overseas involving multiple disciplines.other authors: Satoru Hashimoto,Daisuke Hasegawa,Junji Hatakeyama,Naoki Hara,Naoki Higashibeppu,Nana Furushima,Hirotaka Furusono,Yujiro Matsuishi,Tasuku Matsuyama,Yusuke Minematsu,Ryoichi Miyashita,Yuji Miyatake,Megumi Moriyasu,Toru Yamada,Hiroyuki Yamada,Ryo Yamamoto,Takeshi Yoshida,Yuhei Yoshida,Jumpei Yoshimura,Ryuichi Yotsumoto,Hiroshi Yonekura,Takeshi Wada,Eizo Watanabe,Makoto Aoki,Hideki Asai,Takakuni Abe,Yutaka Igarashi,Naoya Iguchi,Masami Ishikawa,Go Ishimaru,Shutaro Isokawa,Ryuta Itakura,Hisashi Imahase,Haruki Imura,Takashi Irinoda,Kenji Uehara,Noritaka Ushio,Takeshi Umegaki,Yuko Egawa,Yuki Enomoto,Kohei Ota,Yoshifumi Ohchi,Takanori Ohno,Hiroyuki Ohbe,Kazuyuki Oka,Nobunaga Okada,Yohei Okada,Hiromu Okano,Jun Okamoto,Hiroshi Okuda,Takayuki Ogura,Yu Onodera,Yuhta Oyama,Motoshi Kainuma,Eisuke Kako,Masahiro Kashiura,Hiromi Kato,Akihiro Kanaya,Tadashi Kaneko,Keita Kanehata,Ken-ichi Kano,Hiroyuki Kawano,Kazuya Kikutani,Hitoshi Kikuchi,Takahiro Kido,Sho Kimura,Hiroyuki Koami,Daisuke Kobashi,Iwao Saiki,Masahito Sakai,Ayaka Sakamoto,Tetsuya Sato,Yasuhiro Shiga,Manabu Shimoto,Shinya Shimoyama,Tomohisa Shoko,Yoh Sugawara,Atsunori Sugita,Satoshi Suzuki,Yuji Suzuki,Tomohiro Suhara,Kenji Sonota,Shuhei Takauji,Kohei Takashima,Sho Takahashi,Yoko Takahashi,Jun Takeshita,Yuuki Tanaka,Akihito Tampo,Taichiro Tsunoyama,Kenichi Tetsuhara,Kentaro Tokunaga,Yoshihiro Tomioka,Kentaro Tomita,Naoki Tominaga,Mitsunobu Toyosaki,Yukitoshi Toyoda,Hiromichi Naito,Isao Nagata,Tadashi Nagato,Yoshimi Nakamura,Yuki Nakamori,Isao Nahara,Hiromu Naraba,Chihiro Narita,Norihiro Nishioka,Tomoya Nishimura,Kei Nishiyama,Tomohisa Nomura,Taiki Haga,Yoshihiro Hagiwara,Katsuhiko Hashimoto,Takeshi Hatachi,Toshiaki Hamasaki,Takuya Hayashi,Minoru Hayashi,Atsuki Hayamizu,Go Haraguchi,Yohei Hirano,Ryo Fujii,Motoki Fujita,Naoyuki Fujimura,Hiraku Funakoshi,Masahito Horiguchi,Jun Maki,Naohisa Masunaga,Yosuke Matsumura,Takuya Mayumi,Keisuke Minami,Yuya Miyazaki,Kazuyuki Miyamoto,Teppei Murata,Machi Yanai,Takao Yano,Kohei Yamada,Naoki Yamada,Tomonori Yamamoto,Shodai Yoshihiro,Hiroshi Tanaka,Osamu NishidaGuideline

The Japanese Clinical Practice Guidelines for Management of Sepsis and Septic Shock 2020 (J-SSCG 2020)

The Japanese Clinical Practice Guidelines for Management of Sepsis and Septic Shock 2020 (J-SSCG 2020), a Japanese-specific set of clinical practice guidelines for sepsis and septic shock created as revised from J-SSCG 2016 jointly by the Japanese Society of Intensive Care Medicine and the Japanese Association for Acute Medicine, was first released in September 2020 and published in February 2021. An English-language version of these guidelines was created based on the contents of the original Japanese-language version. The purpose of this guideline is to assist medical staff in making appropriate decisions to improve the prognosis of patients undergoing treatment for sepsis and septic shock. We aimed to provide high-quality guidelines that are easy to use and understand for specialists, general clinicians, and multidisciplinary medical professionals. J-SSCG 2016 took up new subjects that were not present in SSCG 2016 (e.g., ICU-acquired weakness [ICU-AW], post-intensive care syndrome [PICS], and body temperature management). The J-SSCG 2020 covered a total of 22 areas with four additional new areas (patient- and family-centered care, sepsis treatment system, neuro-intensive treatment, and stress ulcers). A total of 118 important clinical issues (clinical questions, CQs) were extracted regardless of the presence or absence of evidence. These CQs also include those that have been given particular focus within Japan. This is a large-scale guideline covering multiple fields; thus, in addition to the 25 committee members, we had the participation and support of a total of 226 members who are professionals (physicians, nurses, physiotherapists, clinical engineers, and pharmacists) and medical workers with a history of sepsis or critical illness. The GRADE method was adopted for making recommendations, and the modified Delphi method was used to determine recommendations by voting from all committee members.other authors: Yasuhiro Norisue, Satoru Hashimoto, Daisuke Hasegawa, Junji Hatakeyama, Naoki Hara, Naoki Higashibeppu, Nana Furushima, Hirotaka Furusono, Yujiro Matsuishi, Tasuku Matsuyama, Yusuke Minematsu, Ryoichi Miyashita, Yuji Miyatake, Megumi Moriyasu, Toru Yamada, Hiroyuki Yamada, Ryo Yamamoto, Takeshi Yoshida, Yuhei Yoshida, Jumpei Yoshimura, Ryuichi Yotsumoto, Hiroshi Yonekura, Takeshi Wada, Eizo Watanabe, Makoto Aoki, Hideki Asai, Takakuni Abe, Yutaka Igarashi, Naoya Iguchi, Masami Ishikawa, Go Ishimaru, Shutaro Isokawa, Ryuta Itakura, Hisashi Imahase, Haruki Imura, Takashi Irinoda, Kenji Uehara, Noritaka Ushio, Takeshi Umegaki, Yuko Egawa, Yuki Enomoto, Kohei Ota, Yoshifumi Ohchi, Takanori Ohno, Hiroyuki Ohbe, Kazuyuki Oka, Nobunaga Okada, Yohei Okada, Hiromu Okano, Jun Okamoto, Hiroshi Okuda, Takayuki Ogura, Yu Onodera, Yuhta Oyama, Motoshi Kainuma, Eisuke Kako, Masahiro Kashiura, Hiromi Kato, Akihiro Kanaya, Tadashi Kaneko, Keita Kanehata, Ken-ichi Kano, Hiroyuki Kawano, Kazuya Kikutani, Hitoshi Kikuchi, Takahiro Kido, Sho Kimura, Hiroyuki Koami, Daisuke Kobashi, Iwao Saiki, Masahito Sakai, Ayaka Sakamoto, Tetsuya Sato, Yasuhiro Shiga, Manabu Shimoto, Shinya Shimoyama, Tomohisa Shoko, Yoh Sugawara, Atsunori Sugita, Satoshi Suzuki, Yuji Suzuki, Tomohiro Suhara, Kenji Sonota, Shuhei Takauji, Kohei Takashima, Sho Takahashi, Yoko Takahashi, Jun Takeshita, Yuuki Tanaka, Akihito Tampo, Taichiro Tsunoyama, Kenichi Tetsuhara, Kentaro Tokunaga, Yoshihiro Tomioka, Kentaro Tomita, Naoki Tominaga, Mitsunobu Toyosaki, Yukitoshi Toyoda, Hiromichi Naito, Isao Nagata, Tadashi Nagato, Yoshimi Nakamura, Yuki Nakamori, Isao Nahara, Hiromu Naraba, Chihiro Narita, Norihiro Nishioka, Tomoya Nishimura, Kei Nishiyama, Tomohisa Nomura, Taiki Haga, Yoshihiro Hagiwara, Katsuhiko Hashimoto, Takeshi Hatachi, Toshiaki Hamasaki, Takuya Hayashi, Minoru Hayashi, Atsuki Hayamizu, Go Haraguchi, Yohei Hirano, Ryo Fujii, Motoki Fujita, Naoyuki Fujimura, Hiraku Funakoshi, Masahito Horiguchi, Jun Maki, Naohisa Masunaga, Yosuke Matsumura, Takuya Mayumi, Keisuke Minami, Yuya Miyazaki, Kazuyuki Miyamoto, Teppei Murata, Machi Yanai, Takao Yano, Kohei Yamada, Naoki Yamada, Tomonori Yamamoto, Shodai Yoshihiro, Hiroshi Tanaka & Osamu Nishid

Diagnostic value of procalcitonin and presepsin for sepsis in critically ill adult patients: a systematic review and meta-analysis

Abstract Background Early and accurate diagnosis of sepsis is challenging. Although procalcitonin and presepsin have been identified as potential biomarkers to differentiate between sepsis and other non-infectious causes of systemic inflammation, the diagnostic accuracy of these biomarkers remains controversial. Herein, we performed a comprehensive meta-analysis to assess the overall diagnostic value of procalcitonin and presepsin for the diagnosis of sepsis. Methods We searched three electronic databases (MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials) for relevant studies. Two authors independently screened articles on the basis of inclusion and exclusion criteria. The pooled sensitivity, specificity, and summary receiver operating characteristic curves were estimated. The quality of evidence for diagnostic accuracy in absolute effects, i.e., the number of true or false positives and true or false negatives, gave a particular pre-test probability. Results We included 19 studies (19 observational studies and no randomized controlled trials) that had enrolled 3012 patients. Analyses of summary receiver operating characteristic curves revealed areas under the receiver operating characteristic curves of 0.84 for procalcitonin and 0.87 for presepsin. The pooled sensitivities and specificities were 0.80 (95% confidence interval 0.75 to 0.84) and 0.75 (95% confidence interval 0.67 to 0.81) for procalcitonin. For presepsin, these values were 0.84 (95% confidence interval 0.80 to 0.88) and 0.73 (95% confidence interval 0.61 to 0.82), respectively. There were no statistically significant differences in both pooled sensitivities (p = 0.48) and specificities (p = 0.57) between procalcitonin and presepsin. Conclusion Our meta-analysis provided evidence that the diagnostic accuracy of procalcitonin and presepsin in detecting infection was similar and that both are useful for early diagnosis of sepsis and subsequent reduction of mortality in critically ill adult patients. Systematic review registration The study was registered in PROSPERO under the registration number CRD42016035784

Personal authentication analysis using finger-vein patterns in patients with connective tissue diseases - Possible association with vascular disease and seasonal change

Objective: To examine how connective tissue diseases affect finger-vein pattern authentication. Methods: The finger-vein patterns of 68 patients with connective tissue diseases and 24 healthy volunteers were acquired. Captured as CCD (charge-coupled device) images by transmitting near-infrared light through fingers, they were followed up in once in each season for one year. The similarity of the follow-up patterns and the initial one was evaluated in terms of their normalized cross-correlation C. Results: The mean C values calculated for patients tended to be lower than those calculated for healthy volunteers. In midwinter (February in Japan) they showed statistically significant reduction both as compared with patients in other seasons and as compared with season-matched healthy controls, whereas the values calculated for healthy controls showed no significant seasonal changes. Values calculated for patients with systemic sclerosis (SSc) or mixed connective tissue disease (MCTD) showed major reductions in November and, especially, February. Patients with rheumatoid arthritis (RA) and patients with dermatomyositis or polymyositis (DM/PM) did not show statistically significant seasonal changes in C values. Conclusions: Finger-vein patterns can be used throughout the year to identify patients with connective tissue diseases, but some attention is needed for patients with advanced disease such as SSc

Gastrointestinal polyposis with esophageal polyposis is useful for early diagnosis of Cowden’s disease

Cowden’s disease, one of the several hamartoma syndromes, is characterized by hyperplastic lesions and hamartomas distributed in the whole body. About thirty percent of patients with Cowden’s disease have been reported to be complicated by malignant tumors. Based on the criteria of the International Cowden Consortium, this disease is mainly diagnosed as trichilemmoma of the face and oral mucosal papillomatosis. However, Cowden’s disease patients themselves often do not recognize trichilemmoma of the face and oral mucosal papillomatosis. We report a case of Cowden's disease in a 33-year-old female patient who was diagnosed based on the characteristic findings at gastrointestinal endoscopy. Clinically, the patient was aware of having bloody stools. Multiple polyps found endoscopically in the esophagus, stomach, ileum, colon and rectum showed histopathologically hamartomatous changes and epithelial hyperplasia. Physical examination revealed oral papillomatosis and facial trichilemmomas. A germline mutation in exon 8 of the phosphatase and tensin homolog deleted on chromosome ten (PTEN) gene was found in this case. It was a point mutation of C to T at codon 1003 (CGA→TGA, arginine→stop codon). The characteristic findings on gastrointestinal endoscopy led us to a diagnosis of Cowden’s disease. It has been reported that gastrointestinal polyposis with esophageal polyposis is found in about 85.7% of Japanese patients with Cowden’s disease. The characteristic findings on gastrointestinal endoscopy can be a useful diagnostic clue to Cowden's disease

Phase planes of emergent cycles between 17- and 13-year cycles when 13-year gene is dominant.

<p>(A) Without an Allee effect (<i>N_c</i> = 0). (B) With an Allee effect (<i>N_c</i> = 100). (C) Under varied Allee effects (<i>N_c</i> = 0∼100) and a constant initial population size (<i>N_INI</i> = 1,000). (D) Phase plane of non-cycle genes. The percent genes originated from 17(13)-year broods are shown in Blue (Orange). Other parameters are <i>r</i> = 1.001 and <i>t</i> = 10,000.</p

Phase planes of emergent cycles between 17- and 13-year cycles when 17-year gene is dominant.

<p>(A) Without an Allee effect (<i>N_c</i> = 0). (B) With an Allee effect (<i>N_c</i> = 100). (C) Under varied Allee effects (<i>N_c</i> = 0∼100) and a constant initial population size (<i>N_INI</i> = 1,000). (D) Phase plane of non-cycle genes. The percent genes originated from 17(13)-year broods are shown in Blue (Orange). Other parameters are <i>r</i> = 1.001 and <i>t</i> = 10,000.</p