Genetic parameters for novel mastitis traits defined by combining test-day somatic cell score and differential somatic cell count in the first lactation of Japanese Holsteins.

In this study, we aimed to improve current udder health genetic evaluations by addressing the limitations of monthly sampled somatic cell score (SCS) for distinguishing cows with robust innate immunity from those susceptible to chronic infections. The objectives were to (1) establish novel somatic cell traits by integrating SCS and the differential somatic cell count (DSCC), which represents the combined proportion of polymorphonuclear leukocytes and lymphocytes in somatic cells and (2) estimate genetic parameters for the new traits, including their daily heritability and genetic correlations with milk production traits and SCS, using a random regression test-day model (RRTDM). We derived 3 traits, termed ML_SCS_DSCC, SCS_4_DSCC_65_binary, and ML_SCS_DSCC_binary, by using milk loss (ML) estimates at corresponding SCS and DSCC levels, thresholds established in previous studies, and a threshold established from milk loss estimates, respectively. Data consisted of test-day records collected during January 2021 through March 2022 from 265 herds in Hokkaido, Japan. From these records, we extracted records between 7 to 305 d in milk (DIM) in the first lactation to fit the RRTDM. The model included the random effect of herd-test-day, the fixed effect of year-month, fixed lactation curves nested with calving age groups, and random regressions with Legendre polynomials of order 3 for additive genetic and permanent environmental effects. The analysis was performed using Gibbs sampling with Gibbsf90+ software. The averages (ranges) of the daily heritability estimates over lactation were 0.086 (0.075-0.095) for SCS, 0.104 (0.073-0.127) for ML_SCS_DSCC, 0.137 (0.014-0.297) for SCS_4_DSCC_65_binary, and 0.138 (0.115-0.185) for ML_SCS_DSCC_binary; the heritability curve for SCS_4_DSCC_65_binary was erratic. Genetic correlations within the trait decreased as the DIM interval widened, especially for those integrating DSCC, indicating that these traits should be analyzed using RRTDM rather than repeatability models. The averages (ranges) of genetic correlations with milk yield over lactation were 0.01 (-0.22 to 0.28) for SCS, -0.05 (-0.40 to 0.13) for ML_SCS_DSCC, -0.08 (-0.17 to 0.09) for SCS_4_DSCC_65_binary, and -0.08 (-0.22 to 0.27) for ML_SCS_DSCC_binary. Compared with SCS, the newly defined traits exhibited slightly stronger negative genetic correlations with milk yield. Especially in late lactation stages, the genetic correlation between ML_SCS_DSCC and milk yield was significantly below zero, with a posterior median of -0.40. Furthermore, the new traits showed positive correlations with SCS, having estimates varying from 0.68 to 0.85 for ML_SCS_DSCC, 0.14 to 0.47 for SCS_4_DSCC_65_binary, and 0.61 to 0.66 for ML_SCS_DSCC_binary, depending on DIM. Considering that ML_SCS_DSCC and ML_SCS_DSCC_binary have relatively high heritability (compared with SCS) and favorable genetic correlations with milk production traits and SCS, their incorporation into breeding programs appears promising. Nevertheless, their genetic relationships with (sub)clinical mastitis require further investigation.

Estimating the nonlinear interaction between somatic cell score and differential somatic cell count on milk production by parity using generalized additive models.

This observational study aimed to use somatic cell score (SCS) and differential somatic cell count (DSCC), the combined proportion of polymorphonuclear leukocytes and lymphocytes in somatic cells, to investigate how mastitis affected milk production. Using generalized additive models, we analyzed 50,618 test-day records from 8,081 lactations from 7,912 cows in 197 herds between January 2021 and March 2022 to estimate the nonlinear interaction between SCS and DSCC, and the effects of lactation stages and seasons on milk yield, milk component percentages, and milk component yields by parity of cows. The results show that the interaction between SCS and DSCC on these traits was significant, nonlinear, and complex. When DSCC was high, the negative effects of SCS were minimal, even when SCS reached 8 (i.e., 3,200,000 somatic cells/mL). Cows with high DSCC could have milk yields similar to healthy cows, implying that these cows may have been in the early stages of mastitis and that the milk yield had yet to be affected. Contrastingly, when DSCC was low, milk loss due to high SCS was drastic, especially for cows in third or later lactations, whose milk yield could reduce from more than 35 kg/d to less than 15 kg/d (-59.9%). This tremendous milk loss in high-parity cows was likely due to their higher milk yield and higher risks of chronic mastitis. High SCS and low DSCC also led to a pronounced change in milk composition. The decrease in the percentage of lactose can be directly related to the damage of inflammation to the mammary gland, while the increase in fat and protein percentages was more attributable to the concentration effect resulting from the reduced milk yield. Compared with analyses based on categorized SCS and DSCC values, modeling these 2 indices directly helps us more precisely assess mastitis effects on milk yield and milk composition. For efficient milk production, our results indicate that we should prevent high-parity cows from entering a state of high SCS and low DSCC.

Impact of salt intake on urinary albumin excretion in patients with type 2 diabetic nephropathy: a retrospective cohort study based on a generalized additive model.

Diabetic kidney disease is an important and common cause of end-stage renal disease. Measurement of urinary albumin excretion (UAE) requires the diagnosis of the stage of diabetic nephropathy and the prognosis of renal function. We aimed to analyze the impact of lifestyle modification on UAE in patients with stage 2 and 3 type 2 diabetic nephropathy who received comprehensive medical care, using a generalized additive model (GAM), an explanatory machine learning model. In this retrospective observational study, we used changes in HbA1c, systolic blood pressure (SBP), and diastolic blood pressure (DBP) levels; body mass index (BMI); and daily salt intake as factors contributing to changes in UAE. In total, 269 patients with type 2 diabetic nephropathy were enrolled (stage 2, 217 patients; stage 3, 52 patients). The rankings that contributed to changes in UAE over 6 months by permutation importance were the changes in daily salt intake, HbA1c, SBP, DBP, and BMI. GAM, which predicts the change in UAE, showed that with increase in the changes in salt intake, SBP, and HbA1c, the delta UAE tended to increase. Salt intake was the most contributory factor for the changes in UAE, and daily salt intake was the best lifestyle factor to explain the changes in UAE. Strict control of salt intake may have beneficial effects on improving UAE in patients with stage 2 and 3 diabetic nephropathy.

Artificial Intelligence in Current Diabetes Management and Prediction.

PURPOSE OF REVIEW: Artificial intelligence (AI) can make advanced inferences based on a large amount of data. The mainstream technologies of the AI boom in 2021 are machine learning (ML) and deep learning, which have made significant progress due to the increase in computational resources accompanied by the dramatic improvement in computer performance. In this review, we introduce AI/ML-based medical devices and prediction models regarding diabetes. RECENT FINDINGS: In the field of diabetes, several AI-/ML-based medical devices and regarding automatic retinal screening, clinical diagnosis support, and patient self-management tool have already been approved by the US Food and Drug Administration. As for new-onset diabetes prediction using ML methods, its performance is not superior to conventional risk stratification models that use statistical approaches so far. Despite the current situation, it is expected that the predictive performance of AI will soon be maximized by a large amount of organized data and abundant computational resources, which will contribute to a dramatic improvement in the accuracy of disease prediction models for diabetes.

Unique hexameric structure of copper-containing nitrite reductase of an anammox bacterium KSU-1.

Anaerobic ammonium oxidation (anammox) and denitrification are two different microbial reactions that form nitrogen gas. The initial step in the anammox reaction-reduction of nitrite to nitric oxide-is thought to be catalyzed by homologs of dissimilatory nitrite reductase, which is known to be involved in denitrification. Here, we reveal the crystal structure of the copper-containing nitrite reductase (CuNIR) of strain KSU-1, an anammox bacterium. CuNIR had a unique homohexameric structure with three disulfide bridges between homotrimers, although the trimer was similar to that of known CuNIRs. Kinetic and mutagenesis analyses suggested that the hexameric structure is important for the electron transfer reaction.

Effect of sodium-glucose cotransporter-2 inhibitors on aldosterone-to-renin ratio in diabetic patients with hypertension: a retrospective observational study.

BACKGROUND: Plasma aldosterone-to-renin ratio (ARR) is popularly used for screening primary aldosteronism (PA). Some medications, including diuretics, are known to have an effect on ARR and cause false-negative and false-positive results in PA screening. Currently, there are no studies on the effects of sodium-glucose cotransporter-2 (SGLT2) inhibitors, which are known to have diuretic effects, on ARR. We aimed to investigate the effects of SGLT2 inhibitors on ARR. METHODS: We employed a retrospective design; the study was conducted from April 2016 to December 2018 and carried out in three hospitals. Forty patients with diabetes and hypertension were administered SGLT2 inhibitors. ARR was evaluated before 2 to 6 months after the administration of SGLT2 inhibitors to determine their effects on ARR. RESULTS: No significant changes in the levels of ARR (90.9 ± 51.6 vs. 81.4 ± 62.9) were found. Body mass index, diastolic blood pressure, heart rate, fasting plasma glucose, and hemoglobin A1c were significantly decreased by SGLT2 inhibitors. Serum creatinine was significantly increased. CONCLUSION: SGLT2 inhibitor administration yielded minimal effects on ARR and did not increase false-negative results in PA screening in patients with diabetes and hypertension more than 2 months after administration.

Angiotensin II receptor blocker combined with eplerenone or hydrochlorothiazide for hypertensive patients with diabetes mellitus.

Experimental models recently suggested an interaction between aldosterone and adipose tissue, but clinical investigation has been limited. We studied the effects of eplerenone compared to hydrochlorothiazide (HCTZ) on blood pressure (BP), glucose, and lipid levels in 50 patients with essential hypertension (EHT) and type 2 diabetes mellitus whose BP failed to reach target levels with 8 mg of candesartan alone. BP improved similarly in both groups over the 12-month study period, but BMI, waist circumference, and LDL-cholesterol were decreased in the eplerenone group, while glycohemoglobin was elevated in the HCTZ group.

Inhibition and recovery of continuous electric field application on the activity of anammox biomass.

In this study, the effects of electric field on the activity of anammox biomass were investigated. In batch mode, experimental results demonstrated that the nitrogen removal rate enhanced by 25.6 % compared with the control experiment at the electric field of 2 V/cm with application time of 20 min. However, continuous application (24 h) of electric field impacted a mal-effect on anammox biomass during the intensity between 1 and 4 V/cm. After the electric field was removed, the activity of anammox biomass could recover within 2 weeks. This implied that the mal-effect of electric field on anammox biomass was reversible. The decrease of heme c contents and crude enzyme activity demonstrated to be the main reason for the depress of the anammox biomass activity. Transmission electron microscope observation also proved the morphological change of anammox biomass under electric field.

[A case of advanced gastric cancer with tumor embolus in the portal vein and liver metastasis responding to S-1 plus cisplatin chemotherapy].

A 67-year-old woman presented with anemia. Computed tomography and upper gastrointestinal endoscopy revealed a primary gastric cancer with tumor embolus in the portal vein, liver metastasis, lymph node metastasis, and pancreatic involvement. Because curative surgery was deemed impossible, we started chemotherapy using S-1 (120 mg/m(2)/day for 3 weeks, followed by discontinuation for 2 weeks) plus cisplatin (80 mg/m(2)/day on days 1 and 8). After 4 courses of chemotherapy, the tumor embolus in the portal vein, liver metastasis, lymph node metastasis, and pancreatic involvement had resolved. Therefore, we performed distal gastrectomy. Histological examination revealed ypT1a, ly0, v0, ypN0 (0/49), ypCY0, ypStage IA, with a two-grade histological change in the main tumor after chemotherapy. Postoperatively, she underwent adjuvant chemotherapy with S-1 for 1 year (120 mg/m(2)/day for 4 weeks, followed by discontinuation for 2 weeks). At the 30-month follow-up after the adjuvant chemotherapy, she had no recurrence.

Prediction and causal inference of cardiovascular and cerebrovascular diseases based on lifestyle questionnaires.

Cardiovascular and cerebrovascular diseases (CCVD) are prominent mortality causes in Japan, necessitating effective preventative measures, early diagnosis, and treatment to mitigate their impact. A diagnostic model was developed to identify patients with ischemic heart disease (IHD), stroke, or both, using specific health examination data. Lifestyle habits affecting CCVD development were analyzed using five causal inference methods. This study included 473,734 patients aged ≥ 40 years who underwent specific health examinations in Kanazawa, Japan between 2009 and 2018 to collect data on basic physical information, lifestyle habits, and laboratory parameters such as diabetes, lipid metabolism, renal function, and liver function. Four machine learning algorithms were used: Random Forest, Logistic regression, Light Gradient Boosting Machine, and eXtreme-Gradient-Boosting (XGBoost). The XGBoost model exhibited superior area under the curve (AUC), with mean values of 0.770 (± 0.003), 0.758 (± 0.003), and 0.845 (± 0.005) for stroke, IHD, and CCVD, respectively. The results of the five causal inference analyses were summarized, and lifestyle behavior changes were observed after the onset of CCVD. A causal relationship from 'reduced mastication' to 'weight gain' was found for all causal species theory methods. This prediction algorithm can screen for asymptomatic myocardial ischemia and stroke. By selecting high-risk patients suspected of having CCVD, resources can be used more efficiently for secondary testing.

Development of a fixed-bed anammox reactor with high treatment potential.

A plug-flow type anaerobic ammonium oxidation (anammox) reactor was developed using malt ceramics (MC) produced from carbonized spent grains as the biomass carriers for anammox sludge. Partial nitrified effluent of the filtrate from the sludge dehydrator of a brewery company was used as influent to a 20 L anammox reactor using MC. An average volumetric nitrogen removal rate (VNR) of 8.78 kg-N/m(3)/day was maintained stably for 76 days with 1 h of HRT. In a larger anammox reactor (400 L), an average VNR of 4.84 kg-N/m(3)/day could be maintained for 86 days during the treatment of low strength synthetic inorganic wastewater. As a result of bacterial community analysis for the 20 L anammox reactor, Asahi BRW1, probably originating from the wastewater collected at Asahi Breweries, was detected as the dominant anammox bacterium. These anammox reactors were characterized by a high NH(4)-N removal capacity for low strength wastewater with a short hydraulic retention time.

Mechanical shear contributes to granule formation resulting in quick start-up and stability of a hybrid anammox reactor.

It appears that if suspended biomass washout can be reduced effectively, granule formation will be fastened in fluidized bed. Quicker reactor start-up can be anticipated especially for those system keeping slow growth bacteria such as anammox. A hybrid reactor combined fixed-bed with nonwoven fabrics as biomass carrier and fluidized bed with slow speed mechanical stirring was therefore developed, and its nitrogen removal performances was evaluated experimentally. Only in 38 days, the total nitrogen removal rate (NRR) reached to 1.9 kg(N) m(-3) day (-1) and then doubled within 17 days, with total nitrogen removal efficiency kept above 70%. After 180 days reactor operating, the NRR reached a maximum value of 6.6 kg(N) m(-3) day(-1) and the specific anammox activity was gradually constant in 0.32 kg(N) kg(VSS)(-1) day(-1). Biomass attached on nonwoven fabrics could additionally improve reactor nitrogen removal by 8%. The dominant size of granular sludge reached to 0.78 mm with stirring speed adjusted from 30 to 80 rpm and the hydraulic retention time (HRT) from 8 to 1.5 h during the whole operating time. Scanning electron microscope observation showed especially compact structure of granular sludge. A 70% of anammox bacteria percentage was identified by fluorescence in situ hybridization analysis.

Rapid startup and high rate nitrogen removal from anaerobic sludge digester liquor using a SNAP process.

In this study, a single-stage autotrophic nitrogen removal reactor, packed with a novel acrylic fiber biomass carrier material (Biofix), was applied for nitrogen removal from sludge digester liquor. For rapid start-up, conventional activated sludge was added to the reactor soon after the attachment of anammox biomass on the Biofix carriers, which allowed conventional activated sludge to form a protective layer of biofilm around the anammox biomass. The Nitrogen removal efficiency reached 75% within 1 week at a nitrogen loading rate of 0.46 kg-N/m(3)/day for synthetic wastewater treatment. By the end of the synthetic wastewater treatment period, the maximum nitrogen removal rate had increased to 0.92 kg-N/m(3)/day at a nitrogen loading rate of 1.0 kg-N/m(3)/day. High nitrogen removal rate was also achieved during the actual raw digester liquor treatment with the highest nitrogen removal rate being 0.83 kg-N/m(3)/day at a nitrogen loading rate of 0.93 kg-N/m(3)/day. The thick biofilm on Biofix carriers allowed anammox bacteria to survive under high DO concentration of 5-6 mg/l resulting in stable and high nitrogen removal performance. FISH and CLSM analysis demonstrated that anammox bacteria coexisted and surrounded by ammonium oxidizing bacteria.

High rate nitrogen removal by the CANON process at ambient temperature.

Completely autotrophic nitrogen removal over nitrite (CANON) is a cost-effective nitrogen removal process. Implementation of the CANON process relies on the cooperation of ammonium-oxidizing and Anammox bacteria, as well as the inhibition of nitrite-oxidizing bacteria. Strict limitations on dissolved oxygen (DO) concentration in the reactor, and the addition of sufficient inorganic carbon in the influent, were adopted as the main operational strategies. The reactor was fed with synthetic inorganic wastewater composed mainly of NH(4)(+)-N, and operated for 106 days. Stable nitrogen removal rates (NRR) of around 1.4 kg N m(-3) d(-1) were obtained at ambient temperature. Morphological characteristics and analysis of bacterial community confirmed the formation of functional outer aerobic and inner anaerobic granular sludge, providing evidence of stable nitrogen removal.

[A case of bilingual aphasia with language mixing between Japanese and English caused by superior longitudinal fasciculus lesion-a study using functional MRI and diffusion tensor imaging].

We report a case of left-handed bilingual aphasia with phonemic paraphasia and language mixing from Japanese as a first language to English as a second language. The lesion caused by cerebral infarction was mainly localized in the left parietal lobe white matter. The patient was a 46-year-old, left-handed woman who was bilingual in Japanese and English. Both auditory and visual comprehensions were well maintained after the acute phase of the disease; however, language mixing between Japanese and English was observed during Japanese speech. A pathophysiological interpretation of this case required a focus on the brain network. Our findings suggest that lesions of the superior longitudinal fasciculus and arcuate fasciculus of the white matter fibers just below the left inferior parietal lobule are associated with bilingual aphasia.

Explainable Machine Learning for Atrial Fibrillation in the General Population Using a Generalized Additive Model　- A Cross-Sectional Study.

Background: Atrial fibrillation (AF) is the most common arrhythmia and is associated with increased thromboembolic stroke risk and heart failure. Although various prediction models for AF risk have been developed using machine learning, their output cannot be accurately explained to doctors and patients. Therefore, we developed an explainable model with high interpretability and accuracy accounting for the non-linear effects of clinical characteristics on AF incidence. Methods and Results: Of the 489,073 residents who underwent specific health checkups between 2009 and 2018 and were registered in the Kanazawa Medical Association database, data were used for 5,378 subjects with AF and 167,950 subjects with normal electrocardiogram readings. Forty-seven clinical parameters were combined using a generalized additive model algorithm. We validated the model and found that the area under the curve, sensitivity, and specificity were 0.964, 0.879, and 0.920, respectively. The 9 most important variables were the physical examination of arrhythmia, a medical history of coronary artery disease, age, hematocrit, γ-glutamyl transpeptidase, creatinine, hemoglobin, systolic blood pressure, and HbA1c. Further, non-linear relationships of clinical variables to the probability of AF diagnosis were visualized. Conclusions: We established a novel AF risk explanation model with high interpretability and accuracy accounting for non-linear information obtained at general health checkups. This model contributes not only to more accurate AF risk prediction, but also to a greater understanding of the effects of each characteristic.

Reject water treatment by improvement of whole cell anammox entrapment using polyvinyl alcohol/alginate gel.

Reject water treatment performance was investigated by whole cell anammox sludge entrapped polyvinyl alcohol/sodium alginate gel in the stirred tank reactor (STR). The whole experiment was conducted through Phase 1 and Phase 2 in which synthetic wastewater and modified reject water were used as feeding medium, respectively. The anammox reactor demonstrated quick start-up after 22 days as well as stable and relatively high nitrogen removal rate of more than 8.0 kg-N m(-3) day(-1) during the two both phases even under moderately low temperature of 25 ± 0.5°C during the last 2 months of Phase 2. The matured brownish red PVA beads had good characteristics with buoyant density of 1.10 g cm(-3), settling velocity of 141 m h(-1) and diameter of 4 mm. The bacterial community was identified by 16S rDNA analysis revealing the concurrent existence of KSU-1 and new kind anammox bacterium Kumadai-I after changing influent from synthetic wastewater to reject water. It was speculated that Kumadai-I might play a role as "promotion" factor together with KSU-1 on high nitrogen removal rate. These results demonstrate the potential application of whole cell anammox entrapment by PVA/alginate gel for achieving stable and high-rate nitrogen removal from high ammonium with low C/N ratio contained wastewaters, such as reject water, digester liquor or landfill leachate.

Startup of pilot-scale single-stage nitrogen removal using anammox and partial nitritation (SNAP) reactor for waste brine treatment using marine anammox bacteria.

This study is the first to demonstrate the startup of a pilot-scale single-stage nitrogen removal using anammox and partial nitritation (SNAP) reactor utilizing marine anammox bacteria. A complete mixing type reactor, continuously fed with waste brine obtained from a natural gas plant (salinity 3%, NH4+-N 130-180 mg/L) and having an effective volume of 2 m3, achieved stable operation at temperatures of 20-30°C with a maximum nitrogen removal rate of 1.43 kg-N/m3/day. During the startup process, along with a small amount of seed sludge, granular sludge was additionally inoculated as a biomass carrier for the enrichment of ammonia oxidizing bacteria (AOB), followed by the enrichment of anammox bacteria. A mesh screen equipped at the outlet of the reactor facilitated the successful sludge retention in the reactor. Analysis of bacterial community composition indicated that Candidatus Scalindua was successfully enriched in the pilot SNAP reactor. These methods for stable sludge retention in the reactor greatly contributed to the startup of the first pilot-scale SNAP reactor using marine anammox bacteria.

Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation.

BACKGROUND: Some patients with COVID-19 experienced sudden death due to rapid symptom deterioration. Thus, it is important to predict COVID-19 symptom exacerbation at an early stage prior to increasing severity in patients. Patients with COVID-19 could experience a unique "silent hypoxia" at an early stage of the infection when they are apparently asymptomatic, but with rather low SpO2 (oxygen saturation) levels. In order to continuously monitor SpO2 in daily life, a high-performance wearable device, such as the Apple Watch or Fitbit, has become commercially available to monitor several biometric data including steps, resting heart rate (RHR), physical activity, sleep quality, and estimated oxygen variation (EOV). OBJECTIVE: This study aimed to test whether EOV measured by the wearable device Fitbit can predict COVID-19 symptom exacerbation. METHODS: We recruited patients with COVID-19 from August to November 2020. Patients were asked to wear the Fitbit for 30 days, and biometric data including EOV and RHR were extracted. EOV is a relative physiological measure that reflects users' SpO2 levels during sleep. We defined a high EOV signal as a patient's oxygen level exhibiting a significant dip and recovery within the index period, and a high RHR signal as daily RHR exceeding 5 beats per day compared with the minimum RHR of each patient in the study period. We defined successful prediction as the appearance of those signals within 2 days before the onset of the primary outcome. The primary outcome was the composite of deaths of all causes, use of extracorporeal membrane oxygenation, use of mechanical ventilation, oxygenation, and exacerbation of COVID-19 symptoms, irrespective of readmission. We also assessed each outcome individually as secondary outcomes. We made weekly phone calls to discharged patients to check on their symptoms. RESULTS: We enrolled 23 patients with COVID-19 diagnosed by a positive SARS-CoV-2 polymerase chain reaction test. The patients had a mean age of 50.9 (SD 20) years, and 70% (n=16) were female. Each patient wore the Fitbit for 30 days. COVID-19 symptom exacerbation occurred in 6 (26%) patients. We were successful in predicting exacerbation using EOV signals in 4 out of 5 cases (sensitivity=80%, specificity=90%), whereas the sensitivity and specificity of high RHR signals were 50% and 80%, respectively, both lower than those of high EOV signals. Coincidental obstructive sleep apnea syndrome confirmed by polysomnography was detected in 1 patient via consistently high EOV signals. CONCLUSIONS: This pilot study successfully detected early COVID-19 symptom exacerbation by measuring EOV, which may help to identify the early signs of COVID-19 exacerbation. TRIAL REGISTRATION: University Hospital Medical Information Network Clinical Trials Registry UMIN000041421; https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047290.

A phase I study of high dose camostat mesylate in healthy adults provides a rationale to repurpose the TMPRSS2 inhibitor for the treatment of COVID-19.

Camostat mesylate, an oral serine protease inhibitor, is used to treat chronic pancreatitis and reflux esophagitis. Recently, camostat mesylate and its active metabolite 4-(4-guanidinobenzoyloxy)phenylacetic acid (GBPA) were reported to inhibit the infection of cells by severe acute respiratory syndrome coronavirus 2 by inhibiting type II transmembrane serine protease. We conducted a phase I study to investigate high-dose camostat mesylate as a treatment for coronavirus disease 2019. Camostat mesylate was orally administered to healthy adults at 600 mg 4 times daily under either of the following conditions: fasted state, after a meal, 30 min before a meal, or 1 h before a meal, and the pharmacokinetics and safety profiles were evaluated. In addition, the time of plasma GBPA concentration exceeding the effective concentration was estimated as the time above half-maximal effective concentration (EC50 ) by using pharmacokinetic/pharmacodynamic modeling and simulation. Camostat mesylate was safe and tolerated at all dosages. Compared with the fasted state, the exposure of GBPA after a meal and 30 min before a meal was significantly lower; however, no significant difference was observed at 1 h before a meal. The time above EC50 was 11.5 h when camostat mesylate 600 mg was administered 4 times daily in the fasted state or 1 h before a meal. Based on the results of this phase I study, we are currently conducting a phase III study.