Heat balance analysis for self-heating torrefaction of dairy manure using a mathematical model.

A self-heating torrefaction system was developed to overcome the difficulties in converting high-moisture biomass to biochar. In self-heating torrefaction, the ventilation rate and ambient pressure must be set properly to initiate the process. However, the minimum temperature at which self-heating begins is unclear because the effects of these operating variables on the heat balance are not theoretically understood. The present report presents a mathematical model for the self-heating of dairy manure based on the heat balance equation. The first step was to estimate the heat source; experimental data showed that the activation energy for the chemical oxidation of dairy manure is 67.5 kJ/mol. Next, the heat balance of feedstock in the process was analyzed. Results revealed that the higher the ambient pressure and the lower the ventilation rate at any given pressure, the lower the temperature at which self-heating is induced. The lowest induction temperature was 71 °C at a ventilation rate of 0.05 L min-1 kg-AFS-1 (AFS: ash-free solid). The model also revealed that the ventilation rate significantly affects the heat balance of feedstock and drying rate, suggesting an optimal range for ventilation.

Exploration and Evaluation of Machine Learning-Based Models for Predicting Enzymatic Reactions.

Unannotated gene sequences in databases are increasing due to sequencing advances. Therefore, computational methods to predict functions of unannotated genes are needed. Moreover, novel enzyme discovery for metabolic engineering applications further encourages annotation of sequences. Here, enzyme functions are predicted using two general approaches, each including several machine learning algorithms. First, Enzyme-models (E-models) predict Enzyme Commission (EC) numbers from amino acid sequence information. Second, Substrate-Enzyme models (SE-models) are built to predict substrates of enzymatic reactions together with EC numbers, and Substrate-Enzyme-Product models (SEP-models) are built to predict substrates, products, and EC numbers. While accuracy of E-models is not optimal, SE-models and SEP-models predict EC numbers and reactions with high accuracy using all tested machine learning-based methods. For example, a single Random Forests-based SEP-model predicts EC first digits with an Average AUC score of over 0.94. Various metrics indicate that the current strategy of combining sequence and chemical structure information is effective at improving enzyme reaction prediction.

Impact of nursing experience on cancellation of light sedation for mechanically ventilated patients in a setting of 1 : 2 nurse-patient ratio.

BACKGROUND: Caring for lightly sedated intubated patients increases caregiver workload. Therefore, providing light sedation to intubated patients may depend on nursing experience. We retrospectively investigated the association between conversion from light to deep sedation and nursing experience in intensive care units (ICUs) with a 1 : 2 nurse-to-patient ratio. METHODS: It was a historical cohort study performed in ICUs in a university hospital. One hundred and eighty-four patients requiring more than 72 hours of mechanical ventilation after ICU admission were analyzed. To avoid channeling bias, propensity score analysis was used to generate a set of matched cases (managed by trainee nurses) and controls (managed by experienced nurses), yielding 72 matched patient pairs. Primary (change from light to deep sedation) and secondary outcomes (sedation level after light sedation cancelation, ICU stay, and intubation duration) were compared. RESULTS: Conversion from light to deep sedation was equally preferred by trainee nurses, with conversion rates of > 70% regardless of matching procedure (P = 0.663). Deeper sedation was preferred by experienced nurses (P = 0.025). Management by experienced nurses significantly prolonged ICU stay (16.3 vs. 21.4, P = 0.033). Additional multivariable logistic regression revealed that visual disturbance (OR [95% CI] = 4.3 [1.4-13.3], P = 0.012), Richmond Agitation-Sedation Scale (RASS) (OR [95% CI] = 2.2 [1.7-2.9], P < 0.0001), and dexmedetomidine dose 48 h post-ICU admission (OR [95% CI] = 0.81 [0.69-0.96], P = 0.016) were independently associated with giving up light sedation. CONCLUSIONS: Conversion from light to deep sedation was preferred in > 70% of mechanically ventilated patients in ICUs with a 1 : 2 nurse-to-patient ratio. Rates of sedation level changes for managing mechanically ventilated patients were similar between trainee and experienced nurses. However, experienced nurses preferred significantly deeper sedation than trainee nurses.

Author Correction: Mechanism-based tuning of insect 3,4-dihydroxyphenylacetaldehyde synthase for synthetic bioproduction of benzylisoquinoline alkaloids.

In the original version of this Article, the abbreviation of 3,4-dihydroxyphenylacetaldehyde synthase presented in the first paragraph of the Discussion section was given incorrectly as DYPAA. The correct abbreviation for this enzyme is DHPAAS. This error has been corrected in both the PDF and HTML versions of the Article.

Mechanism-based tuning of insect 3,4-dihydroxyphenylacetaldehyde synthase for synthetic bioproduction of benzylisoquinoline alkaloids.

Previous studies have utilized monoamine oxidase (MAO) and L-3,4-dihydroxyphenylalanine decarboxylase (DDC) for microbe-based production of tetrahydropapaveroline (THP), a benzylisoquinoline alkaloid (BIA) precursor to opioid analgesics. In the current study, a phylogenetically distinct Bombyx mori 3,4-dihydroxyphenylacetaldehyde synthase (DHPAAS) is identified to bypass MAO and DDC for direct production of 3,4-dihydroxyphenylacetaldehyde (DHPAA) from L-3,4-dihydroxyphenylalanine (L-DOPA). Structure-based enzyme engineering of DHPAAS results in bifunctional switching between aldehyde synthase and decarboxylase activities. Output of dopamine and DHPAA products is fine-tuned by engineered DHPAAS variants with Phe79Tyr, Tyr80Phe and Asn192His catalytic substitutions. Balance of dopamine and DHPAA products enables improved THP biosynthesis via a symmetrical pathway in Escherichia coli. Rationally engineered insect DHPAAS produces (R,S)-THP in a single enzyme system directly from L-DOPA both in vitro and in vivo, at higher yields than that of the wild-type enzyme. However, DHPAAS-mediated downstream BIA production requires further improvement.

Total Synthesis of γ-Alkylidenebutenolides, Potent Melanogenesis Inhibitors from Thai Medicinal Plant Melodorum fruticosum.

A hitherto unreported member of γ-alkylidenebutenolides in Melodorum fruticosum (Annonaceae), (4 E)-6-benzoyloxy-7-hydroxy-2,4-heptadiene-4-olide, named as isofruticosinol (4) was isolated from the methanol extract of flowers, along with the known related butenolides, namely, the (4 Z)-isomer (3) of 4, melodrinol (1), and its (4 E)-isomer (2). To unambiguously determine the absolute configuration at the C-6 position in these butenolides, the first total syntheses of both enantiomers of 2-4 were achieved over 6-7 steps from commercially available D- or L-ribose (D- and L-5). Using the same protocol, both enantiomers of 1 were also synthesized. Based on chiral HPLC analysis of all synthetic compounds ( S- and R-1-4), all naturally occurring butenolides were assigned as partial racemic mixtures with respect to the chiral center at C-6 (enantiomeric ratio, 6 S/6 R = ∼83/17). Furthermore, the melanogenesis inhibitory activities of S- and R-1-4 were evaluated, with all shown to be potent inhibitors with IC50 values in the range 0.29-2.9 µM, regardless of differences in the stereochemistry at C-6. In particular, S-4 (IC50 = 0.29 µM) and R-4 (0.39 µM) showed potent inhibitory activities compared with that of reference standard arbutin (174 µM).

M-path: a compass for navigating potential metabolic pathways.

MOTIVATION: Construction of synthetic metabolic pathways promises sustainable production of diverse chemicals and materials. To design synthetic metabolic pathways of high value, computational methods are needed to expand present knowledge by mining comprehensive chemical and enzymatic information databases. Several computational methods have been already reported for the metabolic pathway design, but until now computation complexity has limited the diversity of chemical and enzymatic data used. RESULTS: We introduce a computational platform, M-path, to explore synthetic metabolic pathways including putative enzymatic reactions and compounds. M-path is an iterative random algorithm, which makes efficient use of chemical and enzymatic databases to find potential synthetic metabolic pathways. M-path can readily control the search space and perform well compared with exhaustively enumerating possible pathways. A web-based pathway viewer is also developed to check extensive metabolic pathways with evaluation scores on the basis of chemical similarities. We further produce extensive synthetic metabolic pathways for a comprehensive set of alpha amino acids. The scalable nature of M-path enables us to calculate potential metabolic pathways for any given chemicals.

Visible, safe and certain endotracheal intubation using endoscope system and inhalation anesthesia for rats.

Anesthesia strongly influences laboratory animals, and it can also greatly affect the experimental data. Rats rank only second to mice in the number used in research fields, such as organ transplantation, regenerative medicine and imaging. Therefore, appropriate and effective anesthesia, including the protocol of the endotracheal intubation and inhalation anesthesia, is crucial. Hence, we evaluated these methods in this study. Twelve Wistar rats were intraperitoneally injected with M/M/B: 0.3/4/5, comprising of medetomidine, midazolam and butorphanol at a dose of 0.3 mg/kg + 4.0 mg/kg + 5.0 mg/kg body weight/rat, respectively. An endotracheal tube was then intubated into the trachea. After intubation, the rats were connected to the inhalation anesthesia circuit using isoflurane, and vital signs were measured until 30 min after connection. All intubations were successfully finished within 1 min, and the values of the vital signs were normal and stable. In addition, histopathological observation of the trachea and lungs showed no trauma. These results suggest that this visible endotracheal intubation method is simple, reliable, safe and favorable with regard to the rats' welfare.

New visible endotracheal intubation method using the endoscope system for mice inhalational anesthesia.

Appropriate and effective anesthesia is critical, because it has a strong influence on laboratory animals, and its affect greatly impacts the experimental data. Inhalational anesthesia by endotracheal intubation is currently prevailing in general anesthesia and is prefered over injection anesthesia, especially for large laboratory animals, because it is a safe and easy control agent. However, it is not common for small laboratory animals, because of the high degree of technical skills required. We assessed the capability of use for mice of the endotracheal intubation by using the endoscope system "TESALA AE-C1" and inhalational anesthesia using a ventilator. Endotracheal intubation was successfully performed on all 10 C57BL/6 mice injected with M/M/B: 0.3/4/5 comprised of medetomidine, midazoram and butorphanol, at a dose of 0.3 mg/kg + 4.0 mg/kg + 5.0 mg/kg body weight/mouse, respectively. After the intubated mice were connected with the inhalational anesthesia circuit and the ventilator, vital signs were measured until 15 min after the connection. The data with M/M/B: 0.3/4/5 showed stable and normal values, which indicated that this new endotracheal intubation method was simple, reliable and safe, which mean that this anesthesia is favorable in regard to the animal's welfare.

Analysis of multiple compound-protein interactions reveals novel bioactive molecules.

The discovery of novel bioactive molecules advances our systems-level understanding of biological processes and is crucial for innovation in drug development. For this purpose, the emerging field of chemical genomics is currently focused on accumulating large assay data sets describing compound-protein interactions (CPIs). Although new target proteins for known drugs have recently been identified through mining of CPI databases, using these resources to identify novel ligands remains unexplored. Herein, we demonstrate that machine learning of multiple CPIs can not only assess drug polypharmacology but can also efficiently identify novel bioactive scaffold-hopping compounds. Through a machine-learning technique that uses multiple CPIs, we have successfully identified novel lead compounds for two pharmaceutically important protein families, G-protein-coupled receptors and protein kinases. These novel compounds were not identified by existing computational ligand-screening methods in comparative studies. The results of this study indicate that data derived from chemical genomics can be highly useful for exploring chemical space, and this systems biology perspective could accelerate drug discovery processes.

Identification of a new class of low molecular weight antagonists against the chemokine receptor CXCR4 having the dipicolylamine-zinc(II) complex structure.

Several low molecular weight nonpeptide compounds having the dipicolylamine-zinc(II) complex structure were identified as potent and selective antagonists of the chemokine receptor CXCR4. These compounds showed strong inhibitory activity against CXCL12 binding to CXCR4, and the top compound exhibited significant anti-HIV activity. Zinc(II)-dipicolylamine unit-containing compounds proved to be useful and attractive lead compounds for chemotherapy of these diseases as nonpeptide CXCR4 antagonists possessing the novel scaffold structure.

Structure-activity relationship studies on CXCR4 antagonists having cyclic pentapeptide scaffolds.

Structure-activity relationship studies on CXCR4 antagonists, which were previously found by using cyclic pentapeptide libraries, were performed to optimize side-chain functional groups, involving conformationally constrained analogues. In addition, a new lead of cyclic pentapeptides with the introduction of a novel pharmacophore was developed.

Estimation of sex-age specific clinical reference ranges by nonlinear optimization method.

Most reference ranges are not considered sex-age specific differences. We collected about 700,000 health examination data with 24 items to estimate sex-age specific clinical reference ranges. We proposed nonlinear optimization method as a new method compatible with NCCLS guideline. All items showed sex-age specific differences of reference ranges. Especially, hepatic functions in young aged men and all aged women, diabetic functions in young aged people, blood pressures in older people, and total cholesterol in all aged people might have serious problems. Some abnormal individuals might not be detected using established reference ranges, on the other hand, some normal individuals might be treated excessively.

Screening program of prostate cancer at Tokai University Hospital: characterization of prostate-specific antigen measurement.

A total of 67,214 men participated in screening for prostate cancer (PC) using serum prostate-specific antigen (PSA) from April 1996 to March 2003 at Tokai University Hospital. In 3.5% (2330 / 67,214) of the men, an elevated PSA level (> 4.0 ng/ml) was found and 68.1% (1586/2330) of these subjects were examined at our Urological Outpatient Clinic. Re-testing of PSA showed that 8.4% (133/1586) had a normal level. Needle biopsy of the prostate was performed in 45.2% (633/1453) of the remaining men. As a result, 142 PCs were found and the detection rate was 0.2% (142 / 67,214). The age of the patients with PC was over 50 years. During this period, 135 individuals with voiding dysfunction were also diagnosed as having PC. Comparison of the patients detected by screening with those found at the outpatient clinic revealed significant differences of the age (64.8 vs. 71.9 years, p < 0.0001), serum PSA level (14.6 vs. 154.9 ng/ml, p < 0.0001), and clinical stage (p < 0.0001). In conclusion, a health screening program that includes serum PSA testing is useful for detection of PC at an earlier stage and in younger individuals. We recommend that all men aged 50 years or older undergo testing for PSA to detect PC at an early stage.

Uterine body cancer mass screening at Tokai University Hospital.

A total of 1,512 women participated in mass screenings for uterine body cancer (UBC) from 1998 to 2003 at Tokai University Hospital. Their rate in the examinees of uterine cervical cancer (UCC) mass screenings was 4.7%. Among the 1,512 examinees, endometrial cytological abnormalities (class III or higher) were found in 17 (1.1%) cases. As a result, UBC was detected in two patients (0.13%). One case was diagnosed as class V, adenocarcinoma, and she underwent hysterectomy. In another case, adenocarcinoma was found to be associated with atypical endometrial hyperplasia in hysterectomy specimens. For the remaining 15 cases diagnosed as class III, the cytological abnormalities disappeared after a follow-up except for 3 patients who were not followed at Tokai University Hospital. In a comparison of the examinees with or without genital bleeding, the cytological abnormalities were more frequently detected in the former group; 4.2% (6/142) vs. 0.6% (5/819) (p < 0.05). We recommend examinees aged 40 years or higher with a complaint of genital bleeding to participate in UBC mass screening for detection of endometrial adenocarcinoma at early stages.