This study aimed to evaluate the prognosis of breast cancer patients who received neoadjuvant chemotherapy and underwent sentinel lymph node biopsy (SLNB) alone as axillary surgery regardless of their clinical and pathological lymph node status. We reviewed the records of 1,795 patients from Asan Medical Center who were diagnosed with stage I-III breast cancer and received neoadjuvant chemotherapy during 2003-2014. We selected 760 patients who underwent SLNB alone as axillary surgery and divided these patients into four groups according to their clinical lymph node (cN) and pathological lymph node (pN) status cN(-)pN(-) (n = 377), cN(-)pN(+) (n = 33), cN(+)pN(-) (n = 242), and cN(+)pN(+) (n = 108). We then compared axillary lymph node recurrence, locoregional recurrence (LRR), distant metastasis-free survival (DMFS), and overall survival (OS) among the four groups using Kaplan-Meier analysis. We compared prognosis between the cN(-)pN(-) and cN(+)pN(-) groups to determine whether SLNB alone is an adequate treatment modality even in patients with cN positive pathology before neoadjuvant therapy but SLNB-negative pathology after NAC. The 5-year axillary recurrence rates in the cN(-)pN(-) and cN(+)pN(-) groups were 1.4% and 2.9%, respectively, and there was no significant difference between the two groups (p = 0.152). The axillary recurrence and LRR rates were significantly different among the four groups, with the pN-negative groups (cN[-]pN[-], cN[+]pN[-]) showing lower recurrence rates. DMFS and OS were also significantly different among the four groups, with the cN negative groups (cN[-]pN[-], cN[-]pN[+]) showing improved survival rates. read more Our study findings suggest that SLNB alone was associated with lower LRR rates even in patients with cN positive pathology before neoadjuvant therapy but cN negative pathology after SLNB. Moreover, recurrence and survival rates differ significantly according to clinical and pathological lymph node status.Heat shock proteins (HSPs) play a pivotal role as molecular chaperones against unfavorable conditions. Although HSPs are of great importance, their computational identification remains a significant challenge. Previous studies have two major limitations. First, they relied heavily on amino acid composition features, which inevitably limited their prediction performance. Second, their prediction performance was overestimated because of the independent two-stage evaluations and train-test data redundancy. To overcome these limitations, we introduce two novel deep learning algorithms (1) time-efficient DeepHSP and (2) high-performance DeeperHSP. We propose a convolutional neural network (CNN)-based DeepHSP that classifies both non-HSPs and six HSP families simultaneously. It outperforms state-of-the-art algorithms, despite taking 14-15 times less time for both training and inference. We further improve the performance of DeepHSP by taking advantage of protein transfer learning. While DeepHSP is trained on raw protein sequences, DeeperHSP is trained on top of pre-trained protein representations. Therefore, DeeperHSP remarkably outperforms state-of-the-art algorithms increasing F1 scores in both cross-validation and independent test experiments by 20% and 10%, respectively. We envision that the proposed algorithms can provide a proteome-wide prediction of HSPs and help in various downstream analyses for pathology and clinical research.Quick identification and isolation of SARS-CoV-2 infected individuals is central to managing the COVID-19 pandemic. Real time reverse transcriptase PCR (rRT-PCR) is the gold standard for COVID-19 diagnosis. However, this resource-intensive and relatively lengthy technique is not ideally suited for mass testing. While pooled testing offers substantial savings in cost and time, the size of the optimum pool that offers complete concordance with results of individualized testing remains elusive. To determine the optimum pool size, we first evaluated the utility of pool testing using simulated 5-sample pools with varying proportions of positive and negative samples. We observed that 5-sample pool testing resulted in false negativity rate of 5% when the pools contained one positive sample. We then examined the diagnostic performance of 4-sample pools in the operational setting of a diagnostic laboratory using 500 consecutive samples in 125 pools. With background prevalence of 2.4%, this 4-sample pool testing showed 100% concordance with individualized testing and resulted in 66% and 59% reduction in resource and turnaround time, respectively. Since the negative predictive value of a diagnostic test varies inversely with prevalence, we re-tested the 4-sample pooling strategy using a fresh batch of 500 samples in 125 pools when the prevalence rose to 12.7% and recorded 100% concordance and reduction in cost and turnaround time by 36% and 30%, respectively. These observations led us to conclude that 4-sample pool testing offers the optimal blend of resource optimization and diagnostic performance across difference disease prevalence settings.It is widely recognized that innate macrophage immune reactions to implant debris are central to the inflammatory responses that drive biologic implant failure over the long term. Less common, adaptive lymphocyte immune reactions to implant debris, such as delayed type hypersensitivity (DTH), can also affect implant performance. It is unknown which key patient factors, if any, mediate these adaptive immune responses that potentiate particle/macrophage mediated osteolysis. The objective of this investigation was to determine to what degree known adaptive immune responses to metal implant debris can affect particle-induced osteolysis (PIO); and if this pathomechanism is dependent on 1) innate immune danger signaling, i.e., NLRP3 inflammasome activity, 2) sex, and/or 3) age. We used an established murine calvaria model of PIO using male and female wild-type C57BL/6 vs. Caspase-1 deficient mice as well as young (12-16 weeks old) vs. aged (18-24 months old) female and male C57BL/6 mice. After induction of metal-DTuals should be appropriately assessed and followed for DTH derived peri-implant complications.