[Tumor Lysis Syndrome in a Patient with Germ Cell Tumor : A Case Report].

A 36-year-old man presented to our hospital with right scrotal swelling. A computed tomographic scan revealed a mass in the right scrotum, multiple masses in the lung and liver, and enlarged cervical, mediastinal, and retroperitoneal lymph nodes. After right high orchiectomy, he was diagnosed with nonseminomatous germ cell tumor (pT3N3M1b), with poor risk prediction according to the International Germ Cell Consensus classification. We started chemotherapy with bleomycin, etoposide, and cisplatin. Since serum alphafetoprotein (AFP) and human chorionic gonadotropin (HCG) levels did not decrease to normal levels, second-line chemotherapy with paclitaxel, ifosfamide, and cisplatin was administered. Six days after the start of treatment, the patient became unconscious, and his blood pressure decreased. Seven days later, blood tests revealed high uric acid levels, hyperphosphatemia, and increased creatinine. This was diagnosed as tumor lysis syndrome. Following diagnosis, continuous hemodiafiltration was started, and his condition gradually improved.

Estimation of Respiratory Rate from Thermography Using Respiratory Likelihood Index.

Respiration is a key vital sign used to monitor human health status. Monitoring respiratory rate (RR) under non-contact is particularly important for providing appropriate pre-hospital care in emergencies. We propose an RR estimation system using thermal imaging cameras, which are increasingly being used in the medical field, such as recently during the COVID-19 pandemic. By measuring temperature changes during exhalation and inhalation, we aim to track the respiration of the subject in a supine or seated position in real-time without any physical contact. The proposed method automatically selects the respiration-related regions from the detected facial regions and estimates the respiration rate. Most existing methods rely on signals from nostrils and require close-up or high-resolution images, while our method only requires the facial region to be captured. Facial region is detected using YOLO v3, an object detection model based on deep learning. The detected facial region is divided into subregions. By calculating the respiratory likelihood of each segmented region using the newly proposed index, called the Respiratory Quality Index, the respiratory region is automatically selected and the RR is estimated. An evaluation of the proposed RR estimation method was conducted on seven subjects in their early twenties, with four 15 s measurements being taken. The results showed a mean absolute error of 0.66 bpm. The proposed method can be useful as an RR estimation method.

Autonomous countertraction for secure field of view in laparoscopic surgery using deep reinforcement learning.

PURPOSE: Countertraction is a vital technique in laparoscopic surgery, stretching the tissue surface for incision and dissection. Due to the technical challenges and frequency of countertraction, autonomous countertraction has the potential to significantly reduce surgeons' workload. Despite several methods proposed for automation, achieving optimal tissue visibility and tension for incision remains unrealized. Therefore, we propose a method for autonomous countertraction that enhances tissue surface planarity and visibility. METHODS: We constructed a neural network that integrates a point cloud convolutional neural network (CNN) with a deep reinforcement learning (RL) model. This network continuously controls the forceps position based on the surface shape observed by a camera and the forceps position. RL is conducted in a physical simulation environment, with verification experiments performed in both simulation and phantom environments. The evaluation was performed based on plane error, representing the average distance between the tissue surface and its least-squares plane, and angle error, indicating the angle between the tissue surface vector and the camera's optical axis vector. RESULTS: The plane error decreased under all conditions both simulation and phantom environments, with 93.3% of case showing a reduction in angle error. In simulations, the plane error decreased from 3.6 ± 1.5 mm to 1.1 ± 1.8 mm , and the angle error from 29 ± 19 ∘ to 14 ± 13 ∘ . In the phantom environment, the plane error decreased from 0.96 ± 0.24 mm to 0.39 ± 0.23 mm , and the angle error from 32 ± 29 ∘ to 17 ± 20 ∘ . CONCLUSION: The proposed neural network was validated in both simulation and phantom experimental settings, confirming that traction control improved tissue planarity and visibility. These results demonstrate the feasibility of automating countertraction using the proposed model.

Phylogenetic analyses of Chilomastix and Retortamonas species using in vitro excysted flagellates.

In vitro excystation of cysts of microscopically identified Chilomastix mesnili and Retortamonas sp. isolated from Japanese macaques and Retortamonas sp. isolated from small Indian mongooses could be induced using an established protocol for Giardia intestinalis and subsequently by culturing with H2S-rich Robinson's medium supplemented with Desulfovibrio desulfuricans. Excystation usually began 2 h after incubation in Robinson's medium. DNA was isolated from excysted flagellates after 4 h of incubation or from cultured excysted flagellates. Phylogenetic analysis based on their 18S rRNA genes revealed that two isolates of C. mesnili from Japanese macaques belonged to the same cluster as a C. mesnili isolate from humans, whereas a mammalian Retortamonas sp. isolate from a small Indian mongoose belonged to the same cluster as that of an amphibian Retortamonas spp. isolate from a 'poison arrow frog' [sequence identity to AF439347 (94.9%)]. These results suggest that the sequence homology of the 18S rRNA gene of the two C. mesnili isolates from Japanese macaques was similar to that of humans, in addition to the morphological similarity, and Retortamonas sp. infection of the amphibian type in the small Indian mongoose highlighted the possibility of the effect of host feeding habitats.

Reversible 3D-2D structural phase transition and giant electronic modulation in nonequilibrium alloy semiconductor, lead-tin-selenide.

Material properties depend largely on the dimensionality of the crystal structures and the associated electronic structures. If the crystal-structure dimensionality can be switched reversibly in the same material, then a drastic property change may be controllable. Here, we propose a design route for a direct three-dimensional (3D) to 2D structural phase transition, demonstrating an example in (Pb1-x Sn x )Se alloy system, where Pb2+ and Sn2+ have similar ns2 pseudo-closed shell configurations, but the former stabilizes the 3D rock-salt-type structure while the latter a 2D layered structure. However, this system has no direct phase boundary between these crystal structures under thermal equilibrium. We succeeded in inducing the direct 3D-2D structural phase transition in (Pb1-x Sn x )Se alloy epitaxial films by using a nonequilibrium growth technique. Reversible giant electronic property change was attained at x ~ 0.5 originating in the abrupt band structure switch from gapless Dirac-like state to semiconducting state.