Search

BackgroundThe COVID-19 pandemic has broad negative impact on the physical and mental health of people with chronic neurological disorders such as multiple sclerosis (MS). ObjectiveWe presented a machine learning approach leveraging passive sensor data from smartphones and fitness trackers of people with MS to predict their health outcomes in a natural experiment during a state-mandated stay-at-home period due to a global pandemic. MethodsFirst, we extracted features that capture behavior changes due to the stay-at-home order. Then, we adapted and applied an existing algorithm to these behavior-change features to predict the presence of depression, high global MS symptom burden, severe fatigue, and poor sleep quality during the stay-at-home period. ResultsUsing data collected between November 2019 and May 2020, the algorithm detected depression with an accuracy of 82.5% (65% improvement over baseline; F1-score: 0.84), high global MS symptom burden with an accuracy of 90% (39% improvement over baseline; F1-score: 0.93), severe fatigue with an accuracy of 75.5% (22% improvement over baseline; F1-score: 0.80), and poor sleep quality with an accuracy of 84% (28% improvement over baseline; F1-score: 0.84). ConclusionsOur approach could help clinicians better triage patients with MS and potentially other chronic neurological disorders for interventions and aid patient self-monitoring in their own environment, particularly during extraordinarily stressful circumstances such as pandemics, which would cause drastic behavior changes.

Abstract In this article, a powerful method to synthesize uniform CaCO3 rod bundles with a high mass fraction of aragonite from carbide slag in large‐scale production via a two‐step leaching‐precipitation process is reported. The effects of the addition of ethylene glycol and reaction temperature on the structure and morphology of the prepared CaCO3 samples were investigated and then demonstrated by the experimental results. It is beneficial to increase the mass fraction of aragonite in CaCO3 samples and ensure the formation of regular rod bundles in morphology when the addition of ethylene glycol is 30 mL and the reaction temperature is 80 °C. The formation mechanism of the CaCO3 rod bundles was preliminarily discussed according to the Muffins–Sekerka theory.

Abstract Background Natural killer/T-cell lymphoma (NKTCL) is a disease with limited treatment options and poor outcomes. Daratumumab monotherapy demonstrated clinical activity in a single-patient case report. We present data from the primary analysis of a phase 2 study of daratumumab monotherapy in relapsed or refractory (R/R) NKTCL. Methods This phase 2 study with Simon’s two-stage design evaluated daratumumab in patients with histologically confirmed extranodal NKTCL, nasal type, per WHO classification that was refractory to or relapsed after ≥ 1 line of chemotherapy, who were not candidates for other treatment modalities. All patients received daratumumab 16 mg/kg intravenously once weekly for Cycles 1 and 2, every other week for Cycles 3 through 6, and every 4 weeks thereafter until progression or unacceptable toxicity; all cycles were 28 days. The primary end point was objective response rate (ORR) based on blinded independent central review per Revised Criteria for Response Assessment of Hodgkin and non-Hodgkin Lymphoma (Lugano classification). Results In total, 32 Asian patients received daratumumab. The ORR was 25.0% (95% confidence interval [CI] 11.5–43.4); all 8 responders had a partial response; and the median duration of response was 55.0 days (95% CI 29–339). At 10.2 months of median follow-up, median progression-free survival (PFS) was 53.0 days (95% CI 43–106); the 4-month PFS rate was 13.0%. Median overall survival (OS) was 141.0 days (95% CI 94–438); the 6-month OS rate was 42.9%. Nineteen (59.4%) patients had grade 3/4 treatment-emergent adverse events (TEAEs); the most common was thrombocytopenia (25.0%; n = 8). TEAEs leading to death occurred in 4 patients (death, respiratory failure, septic shock, and pneumonia); all were unrelated to daratumumab. Conclusions In patients with R/R NKTCL, daratumumab monotherapy was well tolerated with no new safety concerns and achieved an ORR of 25.0%. However, no patients achieved complete response, and duration of response was short. Trial registration ClinicalTrials.gov, NCT02927925. Registered 7 October 2016.

Abstract Background The choice of surgery for perianal sepsis is currently controversial. Some people advocate one-time radical surgery for perianal sepsis, while others advocate incision and drainage. The objective of this study is to observe the formation probability of secondary anal fistula after incision and drainage in patients with perianal sepsis and determine factors that contribute to secondary anal fistula after incision and drainage. Methods A retrospective descriptive analysis was conducted in 288 patients with perianal sepsis who were treated with anorectal surgery in the Suzhou Hospital of Traditional Chinese Medicine from January 2016 to June 2018. The patients were followed by telephone, physical examination, and pelvic MRI examination for at least 1 year after surgery. Results Three patients were not followed, 98 patients did not receive surgical treatment or one-time radical surgery for perianal sepsis, and 187 patients were ultimately identified for the study. Anal fistula was present in 105 patients, and the rate of formation of secondary anal fistula was 56.15%. There was no statistically significant difference in the fistula formation rate between different types of sepsis (P>0.05). And, in patients with secondary anal fistula, there was no significant correlation between the location of sepsis and the type of secondary anal fistula (P>0.05). Conclusions The incidence of secondary anal fistula after incision and drainage of perianal sepsis is 56.15%, which is lower than the incidence found in previous study. Young is a risk factor for secondary anal fistula after incision and drainage of perianal sepsis. There is no significant correlation between the location of sepsis and the type of secondary anal fistula. Simple incision and drainage is a suitable choice for patients with acute perianal sepsis.

Based on the impact damper, a dynamic model of a non-fixed constrained collision system was established. The coefficient of restitution is used as the main control parameter to analyze the system’s periodic movement and its bifurcation region. The chattering movement characteristics of the system were revealed. The interval of restitution coefficient for the chattering of collision system under various mass ratio and frequency ratio was obtained. The results show that the chattering phenomenon occurs in the collision system when the coefficient of restitution is greater than 0.5; as the mass ratio decreases, the interval of restitution coefficient for chattering continues to expand; as the frequency increases, the interval of restitution coefficient for chattering narrows.

Green finance is an emerging topic which is broadly discussed in context of adapting and mitigating environmental deterioration due to climate change. As an effective incentive mechanism, it provides strong support for carbon emission reduction. However, a limited review articles investigate the specific combination of green finance and carbon emission reduction. Here, we apply a bibliometric analysis to review research on green finance and carbon emission reduction based on the literature from 2010 to 2021 in the Web of Science core database. The results indicate that countries with the most publications were those with high economic development, salient environmental problems, and a strong demand for ecological protection. Top publishing journals include Climate Policy, Journal of Cleaner Production, and Energy Policy. The author collaboration is fragmented, mostly less than three researchers. Based on analyses of keyword frequency and centrality, deforestation, carbon markets, and financial development were the most significant research topics. The research hotspots included clean development mechanism, adaptation, carbon market, and sequestration. Finally, the DPSIR framework is applied to explore driving forces, state, pressure, impact and response of current research. We hope our work provides a systematic review of green finance for carbon emission reduction to boost the research in this field.

Medicinal plants are inhabited by diverse microbes in every compartment, and which play an essential role in host growth and development, nutrient absorption, synthesis of secondary metabolites, and resistance to biological and abiotic stress. However, the ecological processes that manage microbiota assembly and the phenotypic and metabolic characteristics of the core microbiota of Eucommia ulmoides remain poorly explored. Here, we systematically evaluated the effects of genotypes, compartment niches, and environmental conditions (climate, soil nutrition, and secondary metabolites) on the assembly of rhizosphere soil and bark associated bacterial communities. In addition, phenotypic and metabolic characteristics of E. ulmoides core microbiota, and their relationship with dominant taxa, rare taxa, and pharmacologically active compounds were deciphered. Results suggested that microbiota assembly along the two compartments were predominantly shaped by the environment (especially pH, relative humidity, and geniposide acid) and not by host genotype or compartment niche. There were 690 shared genera in the rhizosphere soil and bark, and the bark microbiota was mainly derived from rhizosphere soil. Core microbiota of E. ulmoides was a highly interactive “hub” microbes connecting dominant and rare taxa, and its phenotypic characteristics had a selective effect on compartment niches. Metabolic functions of the core microbiota included ammonia oxidation, nitrogen fixation, and polyhydroxybutyrate storage, which are closely related to plant growth or metabolism. Moreover, some core taxa were also significantly correlated with three active compounds. These findings provide an important scientific basis for sustainable agricultural management based on the precise regulation of the rhizosphere soil and bark microbiota of E. ulmoides.

Insects have a long history of being used in medicine, with clear primary and secondary functions and less side effects, and the study and exploitation of medicinal insects have received increasing attention. Insects gut microbiota and their metabolites play an important role in protecting the hosts from other potentially harmful microbes, providing nutrients, promoting digestion and degradation, and regulating growth and metabolism of the hosts. However, there are still few studies linking the medicinal values of insects with their gut microbes. In this study, we focused on the specific gut microbiota common to medicinal insects, hoping to trace the potential connection between medicinal values and gut microbes of medicinal insects. Based on 16S rRNA gene sequencing data, we compared the gut microbiota of medicinal insects [Periplaneta americana, Protaetia (Liocola) brevitarsis (Lewis) and Musca domestica], in their medicinal stages, and non-medicinal insects (Hermetia illucens L., Tenebrio molitor, and Drosophila melanogaster), and found that the intestinal microbial richness of medicinal insects was higher, and there were significant differences in the microbial community structure between the two groups. We established a model using a random-forest method to preliminarily screen out several types of gut microbiota common to medicinal insects that may play medicinal values: Parabacteroides goldsteinii, Lactobacillus dextrinicus, Bifidobacterium longum subsp. infantis (B. infantis), and Vagococcus carniphilus. In particular, P. goldsteinii and B. infantis were most probably involved in the anti-inflammatory effects of medicinal insects. Our results revealed an association between medicinal insects and their gut microbes, providing new development directions and possibly potential tools for utilizing microbes to enhance the medicinal efficacy of medicinal insects.

BackgroundAdmissions are generally classified as COVID-19 hospitalizations if the patient has a positive SARS-CoV-2 polymerase chain reaction (PCR) test. However, because 35% of SARS-CoV-2 infections are asymptomatic, patients admitted for unrelated indications with an incidentally positive test could be misclassified as a COVID-19 hospitalization. Electronic health record (EHR)–based studies have been unable to distinguish between a hospitalization specifically for COVID-19 versus an incidental SARS-CoV-2 hospitalization. Although the need to improve classification of COVID-19 versus incidental SARS-CoV-2 is well understood, the magnitude of the problems has only been characterized in small, single-center studies. Furthermore, there have been no peer-reviewed studies evaluating methods for improving classification. ObjectiveThe aims of this study are to, first, quantify the frequency of incidental hospitalizations over the first 15 months of the pandemic in multiple hospital systems in the United States and, second, to apply electronic phenotyping techniques to automatically improve COVID-19 hospitalization classification. MethodsFrom a retrospective EHR-based cohort in 4 US health care systems in Massachusetts, Pennsylvania, and Illinois, a random sample of 1123 SARS-CoV-2 PCR-positive patients hospitalized from March 2020 to August 2021 was manually chart-reviewed and classified as “admitted with COVID-19” (incidental) versus specifically admitted for COVID-19 (“for COVID-19”). EHR-based phenotyping was used to find feature sets to filter out incidental admissions. ResultsEHR-based phenotyped feature sets filtered out incidental admissions, which occurred in an average of 26% of hospitalizations (although this varied widely over time, from 0% to 75%). The top site-specific feature sets had 79%-99% specificity with 62%-75% sensitivity, while the best-performing across-site feature sets had 71%-94% specificity with 69%-81% sensitivity. ConclusionsA large proportion of SARS-CoV-2 PCR-positive admissions were incidental. Straightforward EHR-based phenotypes differentiated admissions, which is important to assure accurate public health reporting and research.

Owing to their excellent photoelectric properties, perovskite materials have broad application prospects; however, the toxicity of Pb limits the application of Pb‐based perovskite materials. To overcome this problem, Pb‐free perovskite materials are prepared by replacing Pb with nontoxic elements including Ge and Sn; nevertheless, the stabilities of these materials are low. Herein, single crystals of nontoxic Cu(I)‐based ternary metal halide (Cs3Cu2Br5) with outstanding stabilities and self‐trapped excition (STE) emission are constructed by an antisolvent method for the first time; these crystals exhibit central blue emission at 458 nm and large Stokes shifts. Photoluminescence (PL) intensities of the single crystals remain above 96.9% of their initial intensities when these crystals are exposed to an atmospheric environment for 90 days. Moreover, the stabilities of the Cs3Cu2Br5 single crystals are investigated by temperature‐dependent PL spectroscopy, which suggests a considerable exciton binding energy of 503 meV, and derivative thermogravimetric analysis, which indicate that the temperature of complete decomposition of Cs3Cu2Br5 is above 930 °C. Furthermore, a new class of white light‐emitting diodes with an ultrahigh color rendering index of 97.8 and satisfactory performance is produced using the Cs3Cu2Br5 single crystals. The study demonstrates significant potentials of Cu(I)‐based single crystals in the field of optoelectronics.