Biofilm formation in living organisms is associated to tissue and implant infections, and it has also been linked to the contribution of antibiotic resistance. Thus, understanding biofilm development and being able to mimic such processes is vital for the successful development of antibiofilm treatments and therapies. Several decades of research have contributed to building the foundation for developing in vitro and in vivo biofilm models. However, no such thing as an ''all fit'' in vitro or in vivo biofilm models is currently available. In this review, in addition to presenting an updated overview of biofilm formation, we critically revise recent approaches for the improvement of in vitro and in vivo biofilm models.

Hirayama disease, also known as Sobue disease is a rare nonprogressive spinal muscular atrophy. Here, we report a case series of three young males presenting with atrophy of distal upper limb and Hirayama disease as their clinico-radiological diagnosis. Magnetic resonance imaging (MRI) revealed loss of cervical lordosis with focal areas of lower cervical cord atrophy in a neutral position. MRI in flexion position revealed, anterior displacement of the detached posterior dura from the underlying lamina compressing the thecal sac and widened posterior epidural space with flow voids seen better on 3D-CISS images. All the three patients were managed conservatively.

Animals are incredibly good at adapting to changes in their environment, a trait envied by most roboticists. Many animals use different gaits to seamlessly transition between land and water and move through non-uniform terrains. In addition to adjusting to changes in their environment, animals can adjust their locomotion to deal with missing or regenerating limbs. Salamanders are an amphibious group of animals that can regenerate limbs, tails, and even parts of the spinal cord in some species. After the loss of a limb, the salamander successfully adjusts to constantly changing morphology as it regenerates the missing part. This quality is of particular interest to roboticists looking to design devices that can adapt to missing or malfunctioning components. While walking, an intact salamander uses its limbs, body, and tail to propel itself along the ground. Its body and tail are coordinated in a distinctive wave-like pattern. Understanding how their bending kinematics change as they regrow lost limbs would provide important information to roboticists designing amphibious machines meant to navigate through unpredictable and diverse terrain. We amputated both hindlimbs of blue-spotted salamanders (Ambystoma laterale) and measured their body and tail kinematics as the limbs regenerated. We quantified the change in the body wave over time and compared them to an amphibious fish species, Polypterus senegalus. We found that salamanders in the early stages of regeneration shift their kinematics, mostly around their pectoral girdle, where there is a local increase in undulation frequency. Amputated salamanders also show a reduced range of preferred walking speeds and an increase in the number of bending waves along the body. This work could assist roboticists working on terrestrial locomotion and water to land transitions.

Depression has been the prime cause of mental-health illness globally. A major depressive disorder is a common mental health disorder that affects both psychologically and physically, which could lead to the loss of life in extreme cases. Detection of depression from the recording of an interview could help with early diagnosis. This paper proposes a three-stage framework multimodal machine learning approach called DepressNet for depression detection using the PHQ-8 Questionnaire score. Bidirectional Long Short-Term Memory (BLSTM) layer network has been proposed, and Extended Distress Analysis Interview Corpus (E-DAIC) dataset was used for the training and validation of the proposed method with the uses multiscale temporal features from audio, video, and text modality and attention mechanisms for fusion. The method achieved the RMSE of 4.32 and CCC of 0.662 on the development set, and on the test set, we got RMSE of 5.36 and CCC of 0.457, outperforming the other methods.

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